NASA Astrophysics Data System (ADS)
Peng, Yu; Wang, Qinghui; Fan, Min
2017-11-01
When assessing re-vegetation project performance and optimizing land management, identification of the key ecological factors inducing vegetation degradation has crucial implications. Rainfall, temperature, elevation, slope, aspect, land use type, and human disturbance are ecological factors affecting the status of vegetation index. However, at different spatial scales, the key factors may vary. Using Helin County, Inner-Mongolia, China as the study site and combining remote sensing image interpretation, field surveying, and mathematical methods, this study assesses key ecological factors affecting vegetation degradation under different spatial scales in a semi-arid agro-pastoral ecotone. It indicates that the key factors are different at various spatial scales. Elevation, rainfall, and temperature are identified as crucial for all spatial extents. Elevation, rainfall and human disturbance are key factors for small-scale quadrats of 300 m × 300 m and 600 m × 600 m, temperature and land use type are key factors for a medium-scale quadrat of 1 km × 1 km, and rainfall, temperature, and land use are key factors for large-scale quadrats of 2 km × 2 km and 5 km × 5 km. For this region, human disturbance is not the key factor for vegetation degradation across spatial scales. It is necessary to consider spatial scale for the identification of key factors determining vegetation characteristics. The eco-restoration programs at various spatial scales should identify key influencing factors according their scales so as to take effective measurements. The new understanding obtained in this study may help to explore the forces which driving vegetation degradation in the degraded regions in the world.
Soil Moisture fusion across scales using a multiscale nonstationary Spatial Hierarchical Model
NASA Astrophysics Data System (ADS)
Kathuria, D.; Mohanty, B.; Katzfuss, M.
2017-12-01
Soil moisture (SM) datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors, on the other hand, provide observations on a finer spatial scale (meter scale or less) but are sparsely available. SM is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables and these interactions change dynamically with footprint scales. Past literature has largely focused on the scale specific effect of these covariates on soil moisture. The present study proposes a robust Multiscale-Nonstationary Spatial Hierarchical Model (MN-SHM) which can assimilate SM from point to RS footprints. The spatial structure of SM across footprints is modeled by a class of scalable covariance functions whose nonstationary depends on atmospheric forcings (such as precipitation) and surface physical controls (such as topography, soil-texture and vegetation). The proposed model is applied to fuse point and airborne ( 1.5 km) SM data obtained during the SMAPVEX12 campaign in the Red River watershed in Southern Manitoba, Canada with SMOS ( 30km) data. It is observed that precipitation, soil-texture and vegetation are the dominant factors which affect the SM distribution across various footprint scales (750 m, 1.5 km, 3 km, 9 km,15 km and 30 km). We conclude that MN-SHM handles the change of support problems easily while retaining reasonable predictive accuracy across multiple spatial resolutions in the presence of surface heterogeneity. The MN-SHM can be considered as a complex non-stationary extension of traditional geostatistical prediction methods (such as Kriging) for fusing multi-platform multi-scale datasets.
[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].
Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping
2016-12-01
As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.
[Spatial scale effect of land use landscape pattern in Yongdeng County, Gansu Province, China.
Liu, Yuan Yuan; Liu, Xue Lu
2016-04-22
Based on "patch-corridor-matrix" pattern, spatial scale effect of landscape pattern was studied in Yongdeng County of Lanzhou City, Gansu Province, China. The results showed that the grassland was the matrix of landscape structure in the studied area, road and river played the corridor role, and the other landscape elements (cultivated land, forest land, garden land, residential land, industrial and mineral land, public management and service land, and the other land) acted as patches. The patch level index and the landscape level index all showed obvious dependence on spatial extent. The scale effect of patch index of different landscape elements existed differently in different extent intervals, so did the scale effect of the landscape level index. Within the extent of 1-20 km, the scale effect showed the most obvious difference between the element types and the index types, while it became smaller in 21-90 km, and disappeared beyond 90 km. 90 km×90 km might be the effective extent to study the dependence of spatial extent of landscape structure.
Spectral characteristics of background error covariance and multiscale data assimilation
Li, Zhijin; Cheng, Xiaoping; Gustafson, Jr., William I.; ...
2016-05-17
The steady increase of the spatial resolutions of numerical atmospheric and oceanic circulation models has occurred over the past decades. Horizontal grid spacing down to the order of 1 km is now often used to resolve cloud systems in the atmosphere and sub-mesoscale circulation systems in the ocean. These fine resolution models encompass a wide range of temporal and spatial scales, across which dynamical and statistical properties vary. In particular, dynamic flow systems at small scales can be spatially localized and temporarily intermittent. Difficulties of current data assimilation algorithms for such fine resolution models are numerically and theoretically examined. Ourmore » analysis shows that the background error correlation length scale is larger than 75 km for streamfunctions and is larger than 25 km for water vapor mixing ratios, even for a 2-km resolution model. A theoretical analysis suggests that such correlation length scales prevent the currently used data assimilation schemes from constraining spatial scales smaller than 150 km for streamfunctions and 50 km for water vapor mixing ratios. Moreover, our results highlight the need to fundamentally modify currently used data assimilation algorithms for assimilating high-resolution observations into the aforementioned fine resolution models. Lastly, within the framework of four-dimensional variational data assimilation, a multiscale methodology based on scale decomposition is suggested and challenges are discussed.« less
Zhang, Ling Yu; Liu, Zhao Gang
2017-12-01
Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.
Scale criticality in estimating ecosystem carbon dynamics
Zhao, Shuqing; Liu, Shuguang
2014-01-01
Scaling is central to ecology and Earth system sciences. However, the importance of scale (i.e. resolution and extent) for understanding carbon dynamics across scales is poorly understood and quantified. We simulated carbon dynamics under a wide range of combinations of resolution (nine spatial resolutions of 250 m, 500 m, 1 km, 2 km, 5 km, 10 km, 20 km, 50 km, and 100 km) and extent (57 geospatial extents ranging from 108 to 1 247 034 km2) in the southeastern United States to explore the existence of scale dependence of the simulated regional carbon balance. Results clearly show the existence of a critical threshold resolution for estimating carbon sequestration within a given extent and an error limit. Furthermore, an invariant power law scaling relationship was found between the critical resolution and the spatial extent as the critical resolution is proportional to An (n is a constant, and A is the extent). Scale criticality and the power law relationship might be driven by the power law probability distributions of land surface and ecological quantities including disturbances at landscape to regional scales. The current overwhelming practices without considering scale criticality might have largely contributed to difficulties in balancing carbon budgets at regional and global scales.
NASA Astrophysics Data System (ADS)
Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.
2003-12-01
The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.
Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal
2016-01-01
The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011–12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales. PMID:28005942
Kajzer-Bonk, Joanna; Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal
2016-01-01
The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011-12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales.
NASA Astrophysics Data System (ADS)
Chen, J. M.; Chen, X.; Ju, W.
2013-03-01
Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shaanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modeled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modeled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI), elevation and aspect have small and additive effects on improving the spatial scaling between these two resolutions.
NASA Astrophysics Data System (ADS)
Chen, J. M.; Chen, X.; Ju, W.
2013-07-01
Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modelled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modelled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI) and elevation have small and additive effects on improving the spatial scaling between these two resolutions.
Mapping spatial patterns of denitrifiers at large scales (Invited)
NASA Astrophysics Data System (ADS)
Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.
2010-12-01
Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.
Guo, X; Fu, B; Ma, K; Chen, L
2000-08-01
Geostatistics combined with GIS was applied to analyze the spatial variability of soil nutrients in topsoil (0-20 cm) in Zunghua City of Hebei Province. GIS can integrate attribute data with geographical data of system variables, which makes the application of geostatistics technique for large spatial scale more convenient. Soil nutrient data in this study included available N (alkaline hydrolyzing nitrogen), total N, available K, available P and organic matter. The results showed that the semivariograms of soil nutrients were best described by spherical model, except for that of available K, which was best fitted by complex structure of exponential model and linear with sill model. The spatial variability of available K was mainly produced by structural factor, while that of available N, total N, available P and organic matter was primarily caused by random factor. However, their spatial heterogeneity degree was different: the degree of total N and organic matter was higher, and that of available P and available N was lower. The results also indicated that the spatial correlation of the five tested soil nutrients at this large scale was moderately dependent. The ranges of available N and available P were almost same, which were 5 km and 5.5 km, respectively. The range of total N was up to 18 km, and that of organic matter was 8.5 km. For available K, the spatial variability scale primarily expressed exponential model between 0-3.5 km, but linear with sill model between 3.5-25.5 km. In addition, five soil nutrients exhibited different isotropic ranges. Available N and available P were isotropic through the whole research range (0-28 km). The isotropic range of available K was 0-8 km, and that of total N and organic matter was 0-10 km.
Effect of spatial averaging on multifractal properties of meteorological time series
NASA Astrophysics Data System (ADS)
Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika
2016-04-01
Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.
Spatial synchrony in cisco recruitment
Myers, Jared T.; Yule, Daniel L.; Jones, Michael L.; Ahrenstorff, Tyler D.; Hrabik, Thomas R.; Claramunt, Randall M.; Ebener, Mark P.; Berglund, Eric K.
2015-01-01
We examined the spatial scale of recruitment variability for disparate cisco (Coregonus artedi) populations in the Great Lakes (n = 8) and Minnesota inland lakes (n = 4). We found that the scale of synchrony was approximately 400 km when all available data were utilized; much greater than the 50-km scale suggested for freshwater fish populations in an earlier global analysis. The presence of recruitment synchrony between Great Lakes and inland lake cisco populations supports the hypothesis that synchronicity is driven by climate and not dispersal. We also found synchrony in larval densities among three Lake Superior populations separated by 25–275 km, which further supports the hypothesis that broad-scale climatic factors are the cause of spatial synchrony. Among several candidate climate variables measured during the period of larval cisco emergence, maximum wind speeds exhibited the most similar spatial scale of synchrony to that observed for cisco. Other factors, such as average water temperatures, exhibited synchrony on broader spatial scales, which suggests they could also be contributing to recruitment synchrony. Our results provide evidence that abiotic factors can induce synchronous patterns of recruitment for populations of cisco inhabiting waters across a broad geographic range, and show that broad-scale synchrony of recruitment can occur in freshwater fish populations as well as those from marine systems.
Knightes, Christopher D.; Golden, Heather E.; Journey, Celeste A.; Davis, Gary M.; Conrads, Paul; Marvin-DiPasquale, Mark; Brigham, Mark E.; Bradley, Paul M.
2014-01-01
Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale mercury data and model simulations can be applied at broader watershed scales using a spatially and temporally explicit watershed hydrology and biogeochemical cycling model, VELMA. We simulate fate and transport using reach-scale (0.1 km2) study data and evaluate applications to multiple watershed scales. Reach-scale VELMA parameterization was applied to two nested sub-watersheds (28 km2 and 25 km2) and the encompassing watershed (79 km2). Results demonstrate that simulated flow and total mercury concentrations compare reasonably to observations at different scales, but simulated methylmercury concentrations are out-of-phase with observations. These findings suggest that intricacies of methylmercury biogeochemical cycling and transport are under-represented in VELMA and underscore the complexity of simulating mercury fate and transport.
NASA Astrophysics Data System (ADS)
Dong, Jingnuo; Ochsner, Tyson E.
2018-03-01
Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.
River eutrophication: irrigated vs. non-irrigated agriculture through different spatial scales.
Monteagudo, Laura; Moreno, José Luis; Picazo, Félix
2012-05-15
The main objective of this study was to determine how spatial scale may affect the results when relating land use to nutrient enrichment of rivers and, secondly, to investigate which agricultural practices are more responsible for river eutrophication in the study area. Agriculture was split into three subclasses (irrigated, non-irrigated and low-impact agriculture) which were correlated to stream nutrient concentration on four spatial scales: large scale (drainage area of total subcatchment and 100 m wide subcatchment corridors) and local scale (5 and 1 km radius buffers). Nitrate, ammonium and orthophosphate concentrations and land use composition (agriculture, urban and forest) were measured at 130 river reaches in south-central Spain during the 2001-2009 period. Results suggested that different spatial scales may lead to different conclusions. Spatial autocorrelation and the inadequate representation of some land uses produced unreal results on large scales. Conversely, local scales did not show data autocorrelation and agriculture subclasses were well represented. The local scale of 1 km buffer was the most appropriate to detect river eutrophication in central Spanish rivers, with irrigated cropland as the main cause of river pollution by nitrate. As regards river management, a threshold of 50% irrigated cropland within a 1 km radius buffer has been obtained using breakpoint regression analysis. This means that no more than 50% of irrigation croplands should be allowed near river banks in order to avoid river eutrophication. Finally, a methodological approach is proposed to choose the appropriate spatial scale when studying river eutrophication caused by diffuse pollution like agriculture. Copyright © 2012 Elsevier Ltd. All rights reserved.
The landscape context of cereal aphid–parasitoid interactions
Thies, Carsten; Roschewitz, Indra; Tscharntke, Teja
2005-01-01
Analyses at multiple spatial scales may show how important ecosystem services such as biological control are determined by processes acting on the landscape scale. We examined cereal aphid–parasitoid interactions in wheat fields in agricultural landscapes differing in structural complexity (32–100% arable land). Complex landscapes were associated with increased aphid mortality resulting from parasitism, but also with higher aphid colonization, thereby counterbalancing possible biological control by parasitoids and lastly resulting in similar aphid densities across landscapes. Thus, undisturbed perennial habitats appeared to enhance both pests and natural enemies. Analyses at multiple spatial scales (landscape sectors of 0.5–6 km diameter) showed that correlations between parasitism and percentage of arable land were significant at scales of 0.5–2 km, whereas aphid densities responded to percentage of arable land at scales of 1–6 km diameter. Hence, the higher trophic level populations appeared to be determined by smaller landscape sectors owing to dispersal limitation, showing the ‘functional spatial scale’ for species-specific landscape management. PMID:15695212
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.
Mapping the distribution of the denitrifier community at large scales (Invited)
NASA Astrophysics Data System (ADS)
Philippot, L.; Bru, D.; Ramette, A.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.
2010-12-01
Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 740 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.
[Spatial scale effect of urban land use landscape pattern in Shanghai City].
Xu, Li-Hua; Yue, Wen Ze; Cao, Yu
2007-12-01
Based on geographic information system (GIS) and remote sensing (RS) techniques, the landscape classes of urban land use in Shanghai City were extracted from SPOT images with 5 m spatial resolution in 2002, and then, the classified data were applied to quantitatively explore the change patterns of several basic landscape metrics at different scales. The results indicated that landscape metrics were sensitive to grain- and extent variance. Urban landscape pattern was spatially dependent. In other words, different landscape metrics showed different responses to scale. The resolution of 40 m was an intrinsic observing scale for urban landscape in Shanghai City since landscape metrics showed random characteristics while the grain was less than 40 m. The extent of 24 km was a symbol scale in a series of extents, which was consistent with the boundary between urban built-up area and suburban area in Shanghai City. As a result, the extent of 12 km away from urban center would be an intrinsic handle scale for urban landscape in Shanghai City. However, due to the complexity of urban structure and asymmetry of urban spatial expansion, the intrinsic handle scale was not regular extent, and the square with size of 24 km was just an approximate intrinsic extent for Shanghai City.
Knightes, C D; Golden, H E; Journey, C A; Davis, G M; Conrads, P A; Marvin-DiPasquale, M; Brigham, M E; Bradley, P M
2014-04-01
Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale mercury data and model simulations can be applied at broader watershed scales using a spatially and temporally explicit watershed hydrology and biogeochemical cycling model, VELMA. We simulate fate and transport using reach-scale (0.1 km(2)) study data and evaluate applications to multiple watershed scales. Reach-scale VELMA parameterization was applied to two nested sub-watersheds (28 km(2) and 25 km(2)) and the encompassing watershed (79 km(2)). Results demonstrate that simulated flow and total mercury concentrations compare reasonably to observations at different scales, but simulated methylmercury concentrations are out-of-phase with observations. These findings suggest that intricacies of methylmercury biogeochemical cycling and transport are under-represented in VELMA and underscore the complexity of simulating mercury fate and transport. Published by Elsevier Ltd.
NASA Astrophysics Data System (ADS)
Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.
2018-03-01
In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.
Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel
2014-01-01
Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes
Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel
2014-01-01
Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes
NASA Astrophysics Data System (ADS)
Sandrini-Neto, L.; Lana, P. C.
2012-06-01
Heterogeneity in the distribution of organisms occurs at a range of spatial scales, which may vary from few centimeters to hundreds of kilometers. The exclusion of small-scale variability from routine sampling designs may confound comparisons at larger scales and lead to inconsistent interpretation of data. Despite its ecological and social-economic importance, little is known about the spatial structure of the mangrove crab Ucides cordatus in the southwest Atlantic. Previous studies have commonly compared densities at relatively broad scales, relying on alleged distribution patterns (e.g., mangroves of distinct composition and structure). We have assessed variability patterns of U. cordatus in mangroves of Paranaguá Bay at four levels of spatial hierarchy (10 s km, km, 10 s m and m) using a nested ANOVA and variance components measures. The potential role of sediment parameters, pneumatophore density, and organic matter content in regulating observed patterns was assessed by multiple regression models. Densities of total and non-commercial size crabs varied mostly at 10 s m to km scales. Densities of commercial size crabs differed at the scales of 10 s m and 10 s km. Variance components indicated that small-scale variation was the most important, contributing up to 70% of the crab density variability. Multiple regression models could not explain the observed variations. Processes driving differences in crab abundance were not related to the measured variables. Small-scale patchy distribution has direct implications to current management practices of U. cordatus. Future studies should consider processes operating at smaller scales, which are responsible for a complex mosaic of patches within previously described patterns.
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
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.
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.
Garrett, Robert G.
2009-01-01
The patterns of relative variability differ by transect and horizon. The N–S transect A-horizon soils show significant between-40-km scale variability for 29 elements, with only 4 elements (Ca, Mg, Pb and Sr) showing in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In contrast, the C-horizon data demonstrate significant between-40-km scale variability for 26 elements, with 21 having in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In 36 instances, the ‘at-site’ variability is statistically significant in terms of the sample preparation and analysis variability. It is postulated that this contrast between the A- and C- horizons along the N–S transect, that is dominated by agricultural land uses, is due to the local homogenization of Ap-horizon soils by tillage reducing the ‘at-site’ variability. The spatial variability is distributed similarly between scales for the A- and C-horizon soils of the E–W transect. For all elements, there is significant variability at the within-40-km scale. Notwithstanding this, there is significant between-40-km variability for 28 and 20 of the elements in the A- and C-horizon data, respectively. The differences between the two transects are attributed to (1) geology, the N–S transect runs generally parallel to regional strikes, whereas the E–W transect runs across regional structures and lithologies; and (2) land use, with agricultural tillage dominating along the N–S transect. The spatial analysis of the transect data indicates that continental-scale maps demonstrating statistically significant patterns of geochemical variability may be prepared for many elements from data on soil samples collected on a 40 x 40 km grid or similar sampling designs resulting in a sample density of 1 site per 1600 km2.
Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai
2016-08-24
This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.
NASA Astrophysics Data System (ADS)
Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai
2016-08-01
This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.
Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai
2016-01-01
This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302–480 km, while the annual precipitation showed smaller scales of 111–182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions. PMID:27553388
Submesoscale Sea Surface Temperature Variability from UAV and Satellite Measurements
NASA Astrophysics Data System (ADS)
Castro, S. L.; Emery, W. J.; Tandy, W., Jr.; Good, W. S.
2017-12-01
Technological advances in spatial resolution of observations have revealed the importance of short-lived ocean processes with scales of O(1km). These submesoscale processes play an important role for the transfer of energy from the meso- to small scales and for generating significant spatial and temporal intermittency in the upper ocean, critical for the mixing of the oceanic boundary layer. Submesoscales have been observed in sea surface temperatures (SST) from satellites. Satellite SST measurements are spatial averages over the footprint of the satellite. When the variance of the SST distribution within the footprint is small, the average value is representative of the SST over the whole pixel. If the variance is large, the spatial heterogeneity is a source of uncertainty in satellite derived SSTs. Here we show evidence that the submesoscale variability in SSTs at spatial scales of 1km is responsible for the spatial variability within satellite footprints. Previous studies of the spatial variability in SST, using ship-based radiometric data suggested that variability at scales smaller than 1 km is significant and affects the uncertainty of satellite-derived skin SSTs. We examine data collected by a calibrated thermal infrared radiometer, the Ball Experimental Sea Surface Temperature (BESST), flown on a UAV over the Arctic Ocean and compare them with coincident measurements from the MODIS spaceborne radiometer to assess the spatial variability of SST within 1 km pixels. By taking the standard deviation of all the BESST measurements within individual MODIS pixels we show that significant spatial variability exists within the footprints. The distribution of the surface variability measured by BESST shows a peak value of O(0.1K) with 95% of the pixels showing σ < 0.45K. More importantly, high-variability pixels are located at density fronts in the marginal ice zone, which are a primary source of submesoscale intermittency near the surface in the Arctic Ocean. Wavenumber spectra of the BESST SSTs indicate a spectral slope of -2, consistent with the presence of submesoscale processes. Furthermore, not only is the BESST wavenumber spectra able to match the MODIS SST spectra well, but also extends the spectral slope of -2 by 2 decades relative to MODIS, from wavelengths of 8km to 0.08km.
NASA Astrophysics Data System (ADS)
Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.
2017-12-01
The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.
An evaluation of the spatial resolution of soil moisture information
NASA Technical Reports Server (NTRS)
Hardy, K. R.; Cohen, S. H.; Rogers, L. K.; Burke, H. H. K.; Leupold, R. C.; Smallwood, M. D.
1981-01-01
Rainfall-amount patterns in the central regions of the U.S. were assessed. The spatial scales of surface features and their corresponding microwave responses in the mid western U.S. were investigated. The usefulness for U.S. government agencies of soil moisture information at scales of 10 km and 1 km. was ascertained. From an investigation of 494 storms, it was found that the rainfall resulting from the passage of most types of storms produces patterns which can be resolved on a 10 km scale. The land features causing the greatest problem in the sensing of soil moisture over large agricultural areas with a radiometer are bodies of water. Over the mid-western portions of the U.S., water occupies less than 2% of the total area, the consequently, the water bodies will not have a significant impact on the mapping of soil moisture. Over most of the areas, measurements at a 10-km resolution would adequately define the distribution of soil moisture. Crop yield models and hydrological models would give improved results if soil moisture information at scales of 10 km was available.
Zajac, R.N.; Lewis, R.S.; Poppe, L.J.; Twichell, D.C.; Vozarik, J.; DiGiacomo-Cohen, M. L.
2003-01-01
Relationships between population abundance and seafloor landscape, or benthoscape, structure were examined for 16 infaunal taxa in eastern Long Island Sound. Based on analyses of a side-scan sonar mosaic, the 19.4-km2 study area was comprised of six distinct large-scale (> km2) benthoscape elements, with varying levels of mesoscale (km2-m2) and small-scale (2) physical and biological habitat heterogeneity. Transition zones among elements varied from ~50 to 200 m in width, comprised ~32% of the benthoscape, and added to overall benthoscape heterogeneity. Population abundances of nine taxa varied significantly among the large-scale elements. Most species were found at high abundances only in one benthoscape element, but three had several foci of elevated abundances. Analyses of population responses to habitat heterogeneity at different spatial scales indicated that abundances of eight taxa varied significantly among spatial scales, but the significant scales were mixed among these species. Relatively large residual variations suggest significant amounts of mesoscale spatial variation were unaccounted for, varying from ~1 km2 to several m2. Responses to transition zones were mixed as well. Abundances of nine taxa varied significantly among transition zones and interiors of benthoscape elements, most with elevated abundances in transition zones. Our results show that infaunal populations exhibit complex and spatially varying patterns of abundance in relation to benthoscape structure and suggest that mesoscale variation may be particularly critical in this regard. Also, transition zones among benthoscape features add considerably to this variation and may be ecological important areas in seafloor environments.
A multi-scale methodology for comparing GCM and RCM results over the Eastern Mediterranean
NASA Astrophysics Data System (ADS)
Samuels, Rana; Krichak, Simon; Breitgand, Joseph; Alpert, Pinhas
2010-05-01
The importance of skillful climate modeling is increasingly being realized as results are being incorporated into environmental, economic, and even business planning. Global circulation models (GCMs) employed by the IPCC provide results at spatial scales of hundreds of kilometers, which is useful for understanding global trends but not appropriate for use as input into regional and local impacts models used to inform policy and development. To address this shortcoming, regional climate models (RCMs) which dynamically downscale the results of the GCMs are used. In this study we present first results of a dynamically downscaled RCM focusing on the Eastern Mediterranean region. For the historical 1960-2000 time period, results at a spatial scale of both 25 km and 50 km are compared with historical station data from 5 locations across Israel as well as with the results of 3 GCM models (ECHAM5, NOAA GFDL, and CCCMA) at annual, monthly and daily time scales. Results from a recently completed Japanese GCM at a spatial scale of 20 km are also included. For the historical validation period, we show that as spatial scale increases the skill in capturing annual and inter-annual temperature and rainfall also increases. However, for intra-seasonal rainfall characteristics important for hydrological and agricultural planning (eg. dry and wet spells, number of rain days) the GCM results (including the 20 km Japanese model) capture the historical trends better than the dynamically downscaled RegCM. For future scenarios of temperature and precipitation changes, we compare results across the models for the available time periods, generating a range of future trends.
The unusual suspect: Land use is a key predictor of biodiversity patterns in the Iberian Peninsula
NASA Astrophysics Data System (ADS)
Martins, Inês Santos; Proença, Vânia; Pereira, Henrique Miguel
2014-11-01
Although land use change is a key driver of biodiversity change, related variables such as habitat area and habitat heterogeneity are seldom considered in modeling approaches at larger extents. To address this knowledge gap we tested the contribution of land use related variables to models describing richness patterns of amphibians, reptiles and passerines in the Iberian Peninsula. We analyzed the relationship between species richness and habitat heterogeneity at two spatial resolutions (i.e., 10 km × 10 km and 50 km × 50 km). Using both ordinary least square and simultaneous autoregressive models, we assessed the relative importance of land use variables, climate variables and topographic variables. We also compare the species-area relationship with a multi-habitat model, the countryside species-area relationship, to assess the role of the area of different types of habitats on species diversity across scales. The association between habitat heterogeneity and species richness varied with the taxa and spatial resolution. A positive relationship was detected for all taxa at a grain size of 10 km × 10 km, but only passerines responded at a grain size of 50 km × 50 km. Species richness patterns were well described by abiotic predictors, but habitat predictors also explained a considerable portion of the variation. Moreover, species richness patterns were better described by a multi-habitat species-area model, incorporating land use variables, than by the classic power model, which only includes area as the single explanatory variable. Our results suggest that the role of land use in shaping species richness patterns goes beyond the local scale and persists at larger spatial scales. These findings call for the need of integrating land use variables in models designed to assess species richness response to large scale environmental changes.
Spatial variability of Chinook salmon spawning distribution and habitat preferences
Cram, Jeremy M.; Torgersen, Christian E.; Klett, Ryan S.; Pess, George R.; May, Darran; Pearsons, Todd N.; Dittman, Andrew H.
2017-01-01
We investigated physical habitat conditions associated with the spawning sites of Chinook Salmon Oncorhynchus tshawytscha and the interannual consistency of spawning distribution across multiple spatial scales using a combination of spatially continuous and discrete sampling methods. We conducted a census of aquatic habitat in 76 km of the upper main-stem Yakima River in Washington and evaluated spawning site distribution using redd survey data from 2004 to 2008. Interannual reoccupation of spawning areas was high, ranging from an average Pearson’s correlation of 0.62 to 0.98 in channel subunits and 10-km reaches, respectively. Annual variance in the interannual correlation of spawning distribution was highest in channel units and subunits, but it was low at reach scales. In 13 of 15 models developed for individual years (2004–2008) and reach lengths (800 m, 3 km, 6 km), stream power and depth were the primary predictors of redd abundance. Multiple channels and overhead cover were patchy but were important secondary and tertiary predictors of reach-scale spawning site selection. Within channel units and subunits, pool tails and thermal variability, which may be associated with hyporheic exchange, were important predictors of spawning. We identified spawning habitat preferences within reaches and channel units that are relevant for salmonid habitat restoration planning. We also identified a threshold (i.e., 2-km reaches) beyond which interannual spawning distribution was markedly consistent, which may be informative for prioritizing habitat restoration or conservation. Management actions may be improved through enhanced understanding of spawning habitat preferences and the consistency with which Chinook Salmon reoccupy spawning areas at different spatial scales.
Insights into mountain precipitation and snowpack from a basin-scale wireless-sensor network
USDA-ARS?s Scientific Manuscript database
A spatially distributed wireless-sensor network, installed across the 2154 km2 portion of the 5311 km2 American River basin above 1500 m elevation, provided spatial measurements of temperature, relative humidity and snow depth. The network consisted of 10 sensor clusters, each with 10 measurement no...
A space-time multifractal analysis on radar rainfall sequences from central Poland
NASA Astrophysics Data System (ADS)
Licznar, Paweł; Deidda, Roberto
2014-05-01
Rainfall downscaling belongs to most important tasks of modern hydrology. Especially from the perspective of urban hydrology there is real need for development of practical tools for possible rainfall scenarios generation. Rainfall scenarios of fine temporal scale reaching single minutes are indispensable as inputs for hydrological models. Assumption of probabilistic philosophy of drainage systems design and functioning leads to widespread application of hydrodynamic models in engineering practice. However models like these covering large areas could not be supplied with only uncorrelated point-rainfall time series. They should be rather supplied with space time rainfall scenarios displaying statistical properties of local natural rainfall fields. Implementation of a Space-Time Rainfall (STRAIN) model for hydrometeorological applications in Polish conditions, such as rainfall downscaling from the large scales of meteorological models to the scale of interest for rainfall-runoff processes is the long-distance aim of our research. As an introduction part of our study we verify the veracity of the following STRAIN model assumptions: rainfall fields are isotropic and statistically homogeneous in space; self-similarity holds (so that, after having rescaled the time by the advection velocity, rainfall is a fully homogeneous and isotropic process in the space-time domain); statistical properties of rainfall are characterized by an "a priori" known multifractal behavior. We conduct a space-time multifractal analysis on radar rainfall sequences selected from the Polish national radar system POLRAD. Radar rainfall sequences covering the area of 256 km x 256 km of original 2 km x 2 km spatial resolution and 15 minutes temporal resolution are used as study material. Attention is mainly focused on most severe summer convective rainfalls. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process. Multifractal analysis is carried out assuming Taylor's hypothesis to hold and the advection velocity needed to rescale the time dimension is assumed to be equal about 16 km/h. This assumption is verified by the analysis of autocorrelation functions along the x and y directions of "rainfall cubes" and along the time axis rescaled with assumed advection velocity. In general for analyzed rainfall sequences scaling is observed for spatial scales ranging from 4 to 256 km and for timescales from 15 min to 16 hours. However in most cases scaling break is identified for spatial scales between 4 and 8, corresponding to spatial dimensions of 16 km to 32 km. It is assumed that the scaling break occurrence at these particular scales in central Poland conditions could be at least partly explained by the rainfall mesoscale gap (on the edge of meso-gamma, storm-scale and meso-beta scale).
Lin, Wei-Chih; Lin, Yu-Pin; Wang, Yung-Chieh; Chang, Tsun-Kuo; Chiang, Li-Chi
2014-02-21
In this study, a deconvolution procedure was used to create a variogram of oral cancer (OC) rates. Based on the variogram, area-to-point (ATP) Poisson kriging and p-field simulation were used to downscale and simulate, respectively, the OC rate data for Taiwan from the district scale to a 1 km × 1 km grid scale. Local cluster analysis (LCA) of OC mortality rates was then performed to identify OC mortality rate hot spots based on the downscaled and the p-field-simulated OC mortality maps. The relationship between OC mortality and land use was studied by overlapping the maps of the downscaled OC mortality, the LCA results, and the land uses. One thousand simulations were performed to quantify local and spatial uncertainties in the LCA to identify OC mortality hot spots. The scatter plots and Spearman's rank correlation yielded the relationship between OC mortality and concentrations of the seven metals in the 1 km cell grid. The correlation analysis results for the 1 km scale revealed a weak correlation between OC mortality rate and concentrations of the seven studied heavy metals in soil. Accordingly, the heavy metal concentrations in soil are not major determinants of OC mortality rates at the 1 km scale at which soils were sampled. The LCA statistical results for local indicator of spatial association (LISA) revealed that the sites with high probability of high-high (high value surrounded by high values) OC mortality at the 1 km grid scale were clustered in southern, eastern, and mid-western Taiwan. The number of such sites was also significantly higher on agricultural land and in urban regions than on land with other uses. The proposed approach can be used to downscale and evaluate uncertainty in mortality data from a coarse scale to a fine scale at which useful additional information can be obtained for assessing and managing land use and risk.
Bayesian Hierarchical Modeling for Big Data Fusion in Soil Hydrology
NASA Astrophysics Data System (ADS)
Mohanty, B.; Kathuria, D.; Katzfuss, M.
2016-12-01
Soil moisture datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors on the other hand provide observations on a finer spatial scale (meter scale or less) but are sparsely available. Soil moisture is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables. Hydrologic processes usually occur at a scale of 1 km or less and therefore spatially ubiquitous and temporally periodic soil moisture products at this scale are required to aid local decision makers in agriculture, weather prediction and reservoir operations. Past literature has largely focused on downscaling RS soil moisture for a small extent of a field or a watershed and hence the applicability of such products has been limited. The present study employs a spatial Bayesian Hierarchical Model (BHM) to derive soil moisture products at a spatial scale of 1 km for the state of Oklahoma by fusing point scale Mesonet data and coarse scale RS data for soil moisture and its auxiliary covariates such as precipitation, topography, soil texture and vegetation. It is seen that the BHM model handles change of support problems easily while performing accurate uncertainty quantification arising from measurement errors and imperfect retrieval algorithms. The computational challenge arising due to the large number of measurements is tackled by utilizing basis function approaches and likelihood approximations. The BHM model can be considered as a complex Bayesian extension of traditional geostatistical prediction methods (such as Kriging) for large datasets in the presence of uncertainties.
NASA Astrophysics Data System (ADS)
Dorrestijn, Jesse; Kahn, Brian H.; Teixeira, João; Irion, Fredrick W.
2018-05-01
Satellite observations are used to obtain vertical profiles of variance scaling of temperature (T) and specific humidity (q) in the atmosphere. A higher spatial resolution nadir retrieval at 13.5 km complements previous Atmospheric Infrared Sounder (AIRS) investigations with 45 km resolution retrievals and enables the derivation of power law scaling exponents to length scales as small as 55 km. We introduce a variable-sized circular-area Monte Carlo methodology to compute exponents instantaneously within the swath of AIRS that yields additional insight into scaling behavior. While this method is approximate and some biases are likely to exist within non-Gaussian portions of the satellite observational swaths of T and q, this method enables the estimation of scale-dependent behavior within instantaneous swaths for individual tropical and extratropical systems of interest. Scaling exponents are shown to fluctuate between β = -1 and -3 at scales ≥ 500 km, while at scales ≤ 500 km they are typically near β ≈ -2, with q slightly lower than T at the smallest scales observed. In the extratropics, the large-scale β is near -3. Within the tropics, however, the large-scale β for T is closer to -1 as small-scale moist convective processes dominate. In the tropics, q exhibits large-scale β between -2 and -3. The values of β are generally consistent with previous works of either time-averaged spatial variance estimates, or aircraft observations that require averaging over numerous flight observational segments. The instantaneous variance scaling methodology is relevant for cloud parameterization development and the assessment of time variability of scaling exponents.
NASA Astrophysics Data System (ADS)
Mishra, Vikalp; Ellenburg, W. Lee; Griffin, Robert E.; Mecikalski, John R.; Cruise, James F.; Hain, Christopher R.; Anderson, Martha C.
2018-06-01
The Soil Moisture Active Passive (SMAP) mission is dedicated toward global soil moisture mapping. Typically, an L-band microwave radiometer has spatial resolution on the order of 36-40 km, which is too coarse for many specific hydro-meteorological and agricultural applications. With the failure of the SMAP active radar within three months of becoming operational, an intermediate (9-km) and finer (3-km) scale soil moisture product solely from the SMAP mission is no longer possible. Therefore, the focus of this study is a disaggregation of the 36-km resolution SMAP passive-only surface soil moisture (SSM) using the Soil Evaporative Efficiency (SEE) approach to spatial scales of 3-km and 9-km. The SEE was computed using thermal-infrared (TIR) estimation of surface evaporation over Continental U.S. (CONUS). The disaggregation results were compared with the 3 months of SMAP-Active (SMAP-A) and Active/Passive (AP) products, while comparisons with SMAP-Enhanced (SMAP-E), SMAP-Passive (SMAP-P), as well as with more than 180 Soil Climate Analysis Network (SCAN) stations across CONUS were performed for a 19 month period. At the 9-km spatial scale, the TIR-Downscaled data correlated strongly with the SMAP-E SSM both spatially (r = 0.90) and temporally (r = 0.87). In comparison with SCAN observations, overall correlations of 0.49 and 0.47; bias of -0.022 and -0.019 and unbiased RMSD of 0.105 and 0.100 were found for SMAP-E and TIR-Downscaled SSM across the Continental U.S., respectively. At 3-km scale, TIR-Downscaled and SMAP-A had a mean temporal correlation of only 0.27. In terms of gain statistics, the highest percentage of SCAN sites with positive gains (>55%) was observed with the TIR-Downscaled SSM at 9-km. Overall, the TIR-based downscaled SSM showed strong correspondence with SMAP-E; compared to SCAN, and overall both SMAP-E and TIR-Downscaled performed similarly, however, gain statistics show that TIR-Downscaled SSM slightly outperformed SMAP-E.
AIR TOXICS MODELING FROM LOCAL TO REGIONAL SCALES TO SUPPORT THE 2002 MULTIPOLLUTANT ASSESSMENT
This research focuses on developing models that can describe the chemical and physical processes affecting concentrations of toxic air pollutants in the atmosphere, at spatial scales, ranging from local (< 1 km) to regional (36 km). One objective of this task is to extend the ca...
Zipf's law from scale-free geometry.
Lin, Henry W; Loeb, Abraham
2016-03-01
The spatial distribution of people exhibits clustering across a wide range of scales, from household (∼10(-2) km) to continental (∼10(4) km) scales. Empirical data indicate simple power-law scalings for the size distribution of cities (known as Zipf's law) and the population density fluctuations as a function of scale. Using techniques from random field theory and statistical physics, we show that these power laws are fundamentally a consequence of the scale-free spatial clustering of human populations and the fact that humans inhabit a two-dimensional surface. In this sense, the symmetries of scale invariance in two spatial dimensions are intimately connected to urban sociology. We test our theory by empirically measuring the power spectrum of population density fluctuations and show that the logarithmic slope α=2.04 ± 0.09, in excellent agreement with our theoretical prediction α=2. The model enables the analytic computation of many new predictions by importing the mathematical formalism of random fields.
NASA Astrophysics Data System (ADS)
Strandgren, J.; Mei, L.; Vountas, M.; Burrows, J. P.; Lyapustin, A.; Wang, Y.
2014-10-01
The Aerosol Optical Depth (AOD) spatial resolution effect is investigated for the linear correlation between satellite retrieved AOD and ground level particulate matter concentrations (PM2.5). The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) for obtaining AOD with a high spatial resolution of 1 km and provides a good dataset for the study of the AOD spatial resolution effect on the particulate matter concentration prediction. 946 Environmental Protection Agency (EPA) ground monitoring stations across the contiguous US have been used to investigate the linear correlation between AOD and PM2.5 using AOD at different spatial resolutions (1, 3 and 10 km) and for different spatial scales (urban scale, meso-scale and continental scale). The main conclusions are: (1) for both urban, meso- and continental scale the correlation between PM2.5 and AOD increased significantly with increasing spatial resolution of the AOD, (2) the correlation between AOD and PM2.5 decreased significantly as the scale of study region increased for the eastern part of the US while vice versa for the western part of the US, (3) the correlation between PM2.5 and AOD is much more stable and better over the eastern part of the US compared to western part due to the surface characteristics and atmospheric conditions like the fine mode fraction.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garten Jr, Charles T; Kang, S.; Brice, Deanne Jane
2007-01-01
The purpose of this research was to test the hypothesis that variability in 11 soil properties, related to soil texture and soil C and N, would increase from small (1 m) to large (1 km) spatial scales in a temperate, mixed-hardwood forest ecosystem in east Tennessee, USA. The results were somewhat surprising and indicated that a fundamental assumption in geospatial analysis, namely that variability increases with increasing spatial scale, did not apply for at least five of the 11 soil properties measured over a 0.5-km2 area. Composite mineral soil samples (15 cm deep) were collected at 1, 5, 10, 50,more » 250, and 500 m distances from a center point along transects in a north, south, east, and westerly direction. A null hypothesis of equal variance at different spatial scales was rejected (P{le}0.05) for mineral soil C concentration, silt content, and the C-to-N ratios in particulate organic matter (POM), mineral-associated organic matter (MOM), and whole surface soil. Results from different tests of spatial variation, based on coefficients of variation or a Mantel test, led to similar conclusions about measurement variability and geographic distance for eight of the 11 variables examined. Measurements of mineral soil C and N concentrations, C concentrations in MOM, extractable soil NH{sub 4}-N, and clay contents were just as variable at smaller scales (1-10 m) as they were at larger scales (50-500 m). On the other hand, measurement variation in mineral soil C-to-N ratios, MOM C-to-N ratios, and the fraction of soil C in POM clearly increased from smaller to larger spatial scales. With the exception of extractable soil NH4-N, measured soil properties in the forest ecosystem could be estimated (with 95% confidence) to within 15% of their true mean with a relatively modest number of sampling points (n{le}25). For some variables, scaling up variation from smaller to larger spatial domains within the ecosystem could be relatively easy because small-scale variation may be indicative of variation at larger scales.« less
Comprehensive geo-spatial data creation for Qassim region in the KSA
NASA Astrophysics Data System (ADS)
Alrajhi, M.; Hawarey, M.
2009-04-01
The General Directorate for Surveying and Mapping (GDSM) of the Deputy Ministry for Land and Surveying (DMLS) of the Ministry of Municipal and Rural Affairs (MOMRA) in the Kingdom of Saudi Arabia (KSA) has the exclusive mandate to carry out aerial photography and produce large-scale detailed maps for about 220 cities and villages in the KSA. This presentation is about the comprehensive geo-spatial data creation for the Qassim region, North KSA, that was founded on country-wide horizontal geodetic ground control using Global Navigation Satellite Systems (GNSS) within the MOMRA's Terrestrial Reference Frame 2000 (MTRF2000) that is tied to International Terrestrial Reference Frame 2000 (ITRF2000) Epoch 2004.0, and vertical geodetic ground control using precise digital leveling in reference to Jeddah 1969 mean sea level, and included aerial photography of 1,505 km2 at 1:5,500 scale, 4,081 km2 at scale 22,500 and 22,224 km2 at 1:45,000 scale, full aerial triangulation, production of orthophoto maps at scale of 1:10,000 (463 sheets) for 22,224 km2, and production of GIS-oriented highly-detailed digital line maps in various formats at scales of 1:1,000 (1,534 sheets) and 1:2,500 (383 sheets) for 1,150 km2, 1:10,000 (161 sheets) for 7,700 km2, and 1:20,000 (130 sheets) for 22,000 km2. While aerial photography lasted from Feb 2003 thru May 2003, the line mapping continued May 2005 until December 2008.
Daniel J. Isaak; Russell F. Thurow
2006-01-01
Spatially continuous sampling designs, when temporally replicated, provide analytical flexibility and are unmatched in their ability to provide a dynamic system view. We have compiled such a data set by georeferencing the network-scale distribution of Chinook salmon (Oncorhynchus tshawytscha) redds across a large wilderness basin (7330 km2) in...
Spatial scale of similarity as an indicator of metacommunity stability in exploited marine systems.
Shackell, Nancy L; Fisher, Jonathan A D; Frank, Kenneth T; Lawton, Peter
2012-01-01
The spatial scale of similarity among fish communities is characteristically large in temperate marine systems: connectivity is enhanced by high rates of dispersal during the larval/juvenile stages and the increased mobility of large-bodied fish. A larger spatial scale of similarity (low beta diversity) is advantageous in heavily exploited systems because locally depleted populations are more likely to be "rescued" by neighboring areas. We explored whether the spatial scale of similarity changed from 1970 to 2006 due to overfishing of dominant, large-bodied groundfish across a 300 000-km2 region of the Northwest Atlantic. Annually, similarities among communities decayed slowly with increasing geographic distance in this open system, but through time the decorrelation distance declined by 33%, concomitant with widespread reductions in biomass, body size, and community evenness. The decline in connectivity stemmed from an erosion of community similarity among local subregions separated by distances as small as 100 km. Larger fish, of the same species, contribute proportionally more viable offspring, so observed body size reductions will have affected maternal output. The cumulative effect of nonlinear maternal influences on egg/larval quality may have compromised the spatial scale of effective larval dispersal, which may account for the delayed recovery of certain member species. Our study adds strong support for using the spatial scale of similarity as an indicator of metacommunity stability both to understand the spatial impacts of exploitation and to refine how spatial structure is used in management plans.
Spatial and Temporal Patterns of Suspended Sediment Yields in Nested Urban Catchments
NASA Astrophysics Data System (ADS)
Kemper, J. T.; Miller, A. J.; Welty, C.
2017-12-01
In a highly regulated area such as the Chesapeake Bay watershed, suspended sediment is a matter of primary concern. Near real-time turbidity and discharge data have been collected continuously for more than four years at five stream gages representing three nested watershed scales (1-2 sq km, 5-6 sq km, 14 sq km) in the highly impervious Dead Run watershed, located in Baltimore County, MD. Using turbidity-concentration relationships based on sample analyses at the gage site, sediment yields for each station can be quantified for a variety of temporal scales. Sediment yields have been calculated for 60+ different storms across four years. Yields show significant spatial variation, both at equivalent sub-watershed scales and from headwaters to mouth. Yields are higher at the headwater station with older development and virtually no stormwater management (DR5) than at the station with more recent development and more extensive stormwater management (DR2). However, this pattern is reversed for the stations at the next larger scale: yields are lower at DR4, downstream of DR5, than at DR3, downstream of DR2. This suggests spatial variation in the dominant sediment sources within each subwatershed. Additionally, C-Q hysteresis curves display consistent counterclockwise behavior at the DR4 station, in contrast to the consistent clockwise behavior displayed at the DR3 station. This further suggests variation in dominant sediment sources (perhaps distal vs local, respectively). We observe consistent seasonal trends in the relative magnitudes of sediment yield for different subwatersheds (e.g. DR3>DR4 in summer, DR5>DR2 in spring). We also observe significant year-to-year variation in sediment yield at the headwater and intermediate scales, whereas yields at the 14 sq km scale are largely similar across the monitored years. This observation would be consistent with the possibility that internal storage and remobilization tend to modulate downstream yields even with spatial and temporal variation in upstream sources. The fine-scale design of this study represents a unique opportunity to compare and contrast sediment yields across a variety of spatial and temporal scales, and provide insight into sediment transport dynamics within an urbanized watershed.
Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales
NASA Astrophysics Data System (ADS)
Abiodun, Olanrewaju O.; Guan, Huade; Post, Vincent E. A.; Batelaan, Okke
2018-05-01
In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000-2005) and 7-year validation period (2007-2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9 % were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.
Temporally and spatially uniform rates of erosion in the southern Appalachian Great Smoky Mountains
Matmon, A.; Bierman, P.R.; Larsen, J.; Southworth, S.; Pavich, M.; Caffee, M.
2003-01-01
We measured 10Be in fluvial sediment samples (n = 27) from eight Great Smoky Mountain drainages (1-330 km2). Results suggest spatially homogeneous sediment generation (on the 104-105 yr time scale and > 100 km2 spatial scale) at 73 ?? 11 t km-2 yr-1, equivalent to 27 ?? 4 m/m.y. of bedrock erosion. This rate is consistent with rates derived from fission-track, long-term sediment budget, and sediment yield data, all of which indicate that the Great Smoky Mountains and the southern Appalachians eroded during the Mesozoic and Cenozoic at ???30 m/m.y. In contrast, unroofing rates during the Paleozoic orogenic events that formed the Appalachian Mountains were higher (???102 m/m.y.). Erosion rates decreased after termination of tectonically driven uplift, enabling the survival of this ancient mountain belt with its deep crustal root as an isostatically maintained feature in the contemporary landscape.
NASA Astrophysics Data System (ADS)
Ba, Yu Tao; xian Liu, Bao; Sun, Feng; Wang, Li hua; Tang, Yu jia; Zhang, Da wei
2017-04-01
High-resolution mapping of PM2.5 is the prerequisite for precise analytics and subsequent anti-pollution interventions. Considering the large variances of particulate distribution, urban-scale mapping is challenging either with ground-based fixed stations, with satellites or via models. In this study, a dynamic fusion method between high-density sensor network and MODIS Aerosol Optical Depth (AOD) was introduced. The sensor network was deployed in Beijing ( > 1000 fixed monitors across 16000 km2 area) to provide raw observations with high temporal resolution (sampling interval < 1 hour), high spatial resolution in flat areas ( < 1 km), and low spatial resolution in mountainous areas ( > 5 km). The MODIS AOD was calibrated to provide distribution map with low temporal resolution (daily) and moderate spatial resolution ( = 3 km). By encoding the data quality and defects (e.g. could, reflectance, abnormal), a hybrid interpolation procedure with cross-validation generated PM2.5 distribution with both high temporal and spatial resolution. Several no-pollutant and high-pollution periods were tested to validate the proposed fusion method for capturing the instantaneous patterns of PM2.5 emission.
NASA Technical Reports Server (NTRS)
Donahue, T. M.; Wasser, B.
1977-01-01
Analysis of OGO-6 OI green line photometer results was carried out for 8 cases when the alignment of the spacecraft was such that local emission rates could be determined below the altitude of maximum emission and down to about 80 km. Results show a variation on a scale of 6 deg to 8 deg in latitude between regions where the emission rate increases rapidly between 90 and 95 km and regions where it increases slowly from 80 km to 95 km. Latitude-altitude maps of iso-emissivity contours and iso-density contours for oxygen concentration are presented. The latter are computed under 3 assumptions concerning excitation mechanisms. Comparisons of the spatial variations of oxygen density with the results of a time dependent theory suggest the regions of strong downward transport alternate on a scale of about 1000 km with regions of weak transport near 90 km. In the first case conversion of O to O3 at night appears to be overwhelmed by downward transport of O.
Interannual evolutions of (sub)mesoscale dynamics in the Bay of Biscay and the English Channel
NASA Astrophysics Data System (ADS)
Charria, G.; Vandermeirsch, F.; Theetten, S.; Yelekçi, Ö.; Assassi, C.; Audiffren, N. J.
2016-02-01
In a context of global change, ocean regions as the Bay of the Biscay and the English Channel represent key domains to estimate the local impact on the coasts of interannual evolutions. Indeed, the coastal (considering in this project regions above the continental shelf) and regional (including the continental slope and the abyssal plain) environments are sensitive to the long-term fluctuations driven by the open ocean, the atmosphere and the watersheds. These evolutions can have impacts on the whole ecosystem. To understand and, by extension, forecast evolutions of these ecosystems, we need to go further in the description and the analysis of the past interannual variability over decadal to pluri-decadal periods. This variability can be described at different spatial scales from small (< 1 km) to basin scales (> 100 km). With a focus on smaller scales, the modelled dynamics, using a Coastal Circulation Model on national computing resources (GENCI/CINES), is discussed from interannual simulations (10 to 53 years) with different spatial (4 km to 1 km) and vertical (40 to 100 sigma levels) resolutions compared with available in situ observations. Exploring vorticity and kinetic energy based diagnostics; dynamical patterns are described including the vertical distribution of the mesoscale activity. Despite the lack of deep and spatially distributed observations, present numerical experiments draw a first picture of the 3D mesoscale distribution and its evolution at interannual time scales.
NASA Astrophysics Data System (ADS)
Zhang, M.; Liu, S.
2017-12-01
Despite extensive studies on hydrological responses to forest cover change in small watersheds, the hydrological responses to forest change and associated mechanisms across multiple spatial scales have not been fully understood. This review thus examined about 312 watersheds worldwide to provide a generalized framework to evaluate hydrological responses to forest cover change and to identify the contribution of spatial scale, climate, forest type and hydrological regime in determining the intensity of forest change related hydrological responses in small (<1000 km2) and large watersheds (≥1000 km2). Key findings include: 1) the increase in annual runoff associated with forest cover loss is statistically significant at multiple spatial scales whereas the effect of forest cover gain is statistically inconsistent; 2) the sensitivity of annual runoff to forest cover change tends to attenuate as watershed size increases only in large watersheds; 3) annual runoff is more sensitive to forest cover change in water-limited watersheds than in energy-limited watersheds across all spatial scales; and 4) small mixed forest-dominated watersheds or large snow-dominated watersheds are more hydrologically resilient to forest cover change. These findings improve the understanding of hydrological response to forest cover change at different spatial scales and provide a scientific underpinning to future watershed management in the context of climate change and increasing anthropogenic disturbances.
Statistical characterization of Earth’s heterogeneities from seismic scattering
NASA Astrophysics Data System (ADS)
Zheng, Y.; Wu, R.
2009-12-01
The distortion of a teleseismic wavefront carries information about the heterogeneities through which the wave propagates and it is manifestited as logarithmic amplitude (logA) and phase fluctuations of the direct P wave recorded by a seismic network. By cross correlating the fluctuations (e.g., logA-logA or phase-phase), we obtain coherence functions, which depend on spatial lags between stations and incident angles between the incident waves. We have mathematically related the depth-dependent heterogeneity spectrum to the observable coherence functions using seismic scattering theory. We will show that our method has sharp depth resolution. Using the HiNet seismic network data in Japan, we have inverted power spectra for two depth ranges, ~0-120km and below ~120km depth. The coherence functions formed by different groups of stations or by different groups of earthquakes at different back azimuths are similar. This demonstrates that the method is statistically stable and the inhomogeneities are statistically stationary. In both depth intervals, the trend of the spectral amplitude decays from large scale to small scale in a power-law fashion with exceptions at ~50km for the logA data. Due to the spatial spacing of the seismometers, only information from length scale 15km to 200km is inverted. However our scattering method provides new information on small to intermediate scales that are comparable to scales of the recycled materials and thus is complimentary to the global seismic tomography which reveals mainly large-scale heterogeneities on the order of ~1000km. The small-scale heterogeneities revealed here are not likely of pure thermal origin. Therefore, the length scale and strength of heterogeneities as a function of depth may provide important constraints in mechanical mixing of various components in the mantle convection.
Bunnell, D.B.; Adams, J.V.; Gorman, O.T.; Madenjian, C.P.; Riley, S.C.; Roseman, E.F.; Schaeffer, J.S.
2010-01-01
Climate and dispersal are the two most commonly cited mechanisms to explain spatial synchrony among time series of animal populations, and climate is typically most important for fishes. Using data from 1978-2006, we quantified the spatial synchrony in recruitment and population catch-per-unit-effort (CPUE) for bloater (Coregonus hoyi) populations across lakes Superior, Michigan, and Huron. In this natural field experiment, climate was highly synchronous across lakes but the likelihood of dispersal between lakes differed. When data from all lakes were pooled, modified correlograms revealed spatial synchrony to occur up to 800 km for long-term (data not detrended) trends and up to 600 km for short-term (data detrended by the annual rate of change) trends. This large spatial synchrony more than doubles the scale previously observed in freshwater fish populations, and exceeds the scale found in most marine or estuarine populations. When analyzing the data separately for within- and between-lake pairs, spatial synchrony was always observed within lakes, up to 400 or 600 km. Conversely, between-lake synchrony did not occur among short-term trends, and for long-term trends, the scale of synchrony was highly variable. For recruit CPUE, synchrony occurred up to 600 km between both lakes Michigan and Huron (where dispersal was most likely) and lakes Michigan and Superior (where dispersal was least likely), but failed to occur between lakes Huron and Superior (where dispersal likelihood was intermediate). When considering the scale of putative bloater dispersal and genetic information from previous studies, we concluded that dispersal was likely underlying within-lake synchrony but climate was more likely underlying between-lake synchrony. The broad scale of synchrony in Great Lakes bloater populations increases their probability of extirpation, a timely message for fishery managers given current low levels of bloater abundance. ?? Springer-Verlag 2009.
Spatial scale of land-use impacts on riverine drinking source water quality
NASA Astrophysics Data System (ADS)
Hurley, Tim; Mazumder, Asit
2013-03-01
Drinking water purveyors are increasingly relying on land conservation and management to ensure the safety of the water that they provide to consumers. To cost-effectively implement any such landscape initiatives, resources must be targeted to the appropriate spatial scale to address quality impairments of concern in a cost-effective manner. Using data gathered from 40 Canadian rivers across four ecozones, we examined the spatial scales at which land use was most closely associated with drinking source water quality metrics. Exploratory linear mixed-effects models accounting for climatic, hydrological, and physiographic variation among sites suggested that different spatial areas of land-use influence drinking source water quality depending on the parameter and season investigated. Escherichia coli spatial variability was only associated with land use at a local (5-10 km) spatial scale. Turbidity measures exhibited a complex association with land use, suggesting that the land-use areas of greatest influence can range from a 1 km subcatchment to the entire watershed depending on the season. Total organic carbon concentrations were only associated with land use characterized at the entire watershed scale. The Canadian Council of Ministers of the Environment Water Quality Index was used to calculate a composite measure of seasonal drinking source water quality but did not provide additional information beyond the analyses of individual parameters. These results suggest that entire watershed management is required to safeguard drinking water sources with more focused efforts at targeted spatial scales to reduce specific risk parameters.
USDA-ARS?s Scientific Manuscript database
We conduct a novel comprehensive investigation that seeks to prove the connection between spatial and time scales in surface soil moisture (SM) within the satellite footprint (~50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies ...
NASA Astrophysics Data System (ADS)
Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.
2011-12-01
The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) has been applied to model the spatial distribution of nitrogen deposition and air concentration over the UK at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.
NASA Astrophysics Data System (ADS)
Dore, A. J.; Kryza, M.; Hall, J. R.; Hallsworth, S.; Keller, V. J. D.; Vieno, M.; Sutton, M. A.
2012-05-01
The Fine Resolution Atmospheric Multi-pollutant Exchange model (FRAME) was applied to model the spatial distribution of reactive nitrogen deposition and air concentration over the United Kingdom at a 1 km spatial resolution. The modelled deposition and concentration data were gridded at resolutions of 1 km, 5 km and 50 km to test the sensitivity of calculations of the exceedance of critical loads for nitrogen deposition to the deposition data resolution. The modelled concentrations of NO2 were validated by comparison with measurements from the rural sites in the national monitoring network and were found to achieve better agreement with the high resolution 1 km data. High resolution plots were found to represent a more physically realistic distribution of reactive nitrogen air concentrations and deposition resulting from use of 1 km resolution precipitation and emissions data as compared to 5 km resolution data. Summary statistics for national scale exceedance of the critical load for nitrogen deposition were not highly sensitive to the grid resolution of the deposition data but did show greater area exceedance with coarser grid resolution due to spatial averaging of high nitrogen deposition hot spots. Local scale deposition at individual Sites of Special Scientific Interest and high precipitation upland sites was sensitive to choice of grid resolution of deposition data. Use of high resolution data tended to generate lower deposition values in sink areas for nitrogen dry deposition (Sites of Scientific Interest) and higher values in high precipitation upland areas. In areas with generally low exceedance (Scotland) and for certain vegetation types (montane), the exceedance statistics were more sensitive to model data resolution.
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.
Elk resource selection at parturition sites, Black Hills, South Dakota
Chadwick P. Lehman; Mark A. Rumble; Christopher T. Rota; Benjamin J. Bird; Dillon T. Fogarty; Joshua J. Millspaugh
2015-01-01
We studied elk (Cervus canadensis nelsoni) parturition sites at coarse (314-km2 and 7-km2) and fine (0.2-ha) scales in the Black Hills, South Dakota, 2011-2013, following a period of population decline and poor calf recruitment. Our objective was to test whether female elk selected parturition sites across spatial scales in association with forage, terrain...
The pyramid system for multiscale raster analysis
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.
Veiga, Puri; Torres, Ana Catarina; Aneiros, Fernando; Sousa-Pinto, Isabel; Troncoso, Jesús S; Rubal, Marcos
2016-09-01
Spatial variability of environmental factors and macrobenthos, using species and functional groups, was examined over the same scales (100s of cm to >100 km) in intertidal sediments of two transitional water systems. The objectives were to test if functional groups were a good species surrogate and explore the relationship between environmental variables and macrobenthos. Environmental variables, diversity and the multivariate assemblage structure showed the highest variability at the scale of 10s of km. However, abundance was more variable at 10s of m. Consistent patterns were achieved using species and functional groups therefore, these may be a good species surrogate. Total carbon, salinity and silt/clay were the strongest correlated with macrobenthic assemblages. Results are valuable for design and interpretation of future monitoring programs including detection of anthropogenic disturbances in transitional systems and propose improvements in environmental variable sampling to refine the assessment of their relationship with biological data across spatial scales. Copyright © 2016 Elsevier Ltd. All rights reserved.
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.
Development of coarse-scale spatial data for wildland fire and fuel management
Kirsten M. Schmidt; James P. Menakis; Colin C. Hardy; Wendall J. Hann; David L. Bunnell
2002-01-01
We produced seven coarse-scale, 1-km2 resolution, spatial data layers for the conterminous United States to support national-level fire planning and risk assessments. Four of these layers were developed to evaluate ecological conditions and risk to ecosystem components: Potential Natural Vegetation Groups, a layer of climax vegetation types representing site...
USDA-ARS?s Scientific Manuscript database
The Western Lake Erie Basin (WLEB) was inundated with precipitation during June and July 2015 (2-3× greater than historical averages), which led to significant nutrient loading and the largest in-lake algal bloom on record. Using discharge and concentration data from three spatial scales (0.09 km2 t...
Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks
NASA Astrophysics Data System (ADS)
Mishra, U.; Riley, W. J.
2015-01-01
The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.
Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks
NASA Astrophysics Data System (ADS)
Mishra, U.; Riley, W. J.
2015-07-01
The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.
Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks
Mishra, U.; Riley, W. J.
2015-07-02
The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less
Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks
Mishra, U.; Riley, W. J.
2015-01-01
The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less
NASA Astrophysics Data System (ADS)
Moghaddam, M.; Silva, A.; Clewley, D.; Akbar, R.; Entekhabi, D.
2013-12-01
Soil Moisture Sensing Controller and oPtimal Estimator (SoilSCAPE) is a wireless in-situ sensor network technology, developed under the support of NASA ESTO/AIST program, for multi-scale validation of soil moisture retrievals from the Soil Moisture Active and Passive (SMAP) mission. The SMAP sensor suite is expected to produce soil moisture retrievals at 3 km scale from the radar instrument, at 36 km from the radiometer, and at 10 km from the combination of the two sensors. To validate the retrieved soil moisture maps at any of these scales, it is necessary to perform in-situ observations at multiple scales (ten, hundreds, and thousands of meters), representative of the true spatial variability of soil moisture fields. The most recent SoilSCAPE network, deployed in the California central valley, has been designed, built, and deployed to accomplish this goal, and is expected to become a core validation site for SMAP. The network consists of up to 150 sensor nodes, each comprised of 3-4 soil moisture sensors at various depths, deployed over a spatial extent of 36 km by 36 km. The network contains multiple sub-networks, each having up to 30 nodes, whose location is selected in part based on maximizing the land cover diversity within the 36 km cell. The network has achieved unprecedented energy efficiency, longevity, and spatial coverage using custom-designed hardware and software protocols. The network architecture utilizes a nested strategy, where a number of end devices (EDs) communicate to a local coordinator (LC) using our recently developed hardware with ultra-efficient circuitry and best-effort-timeslot allocation communication protocol. The LCs in turn communicates with the base station (BS) via text messages and a new compression scheme. The hardware and software technologies required to implement this latest deployment of the SoilSCAPE network will be presented in this paper, and several data sets resulting from the measurements will be shown. The data are available publicly in near-real-time from the project web site, and are also available and searchable via an extensive set of metadata fields through the ORNL-DAAC.
Representation of vegetation by continental data sets derived from NOAA-AVHRR data
NASA Technical Reports Server (NTRS)
Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.
1991-01-01
Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.
Zhang, Zhenming; Zhou, Yunchao; Wang, Shijie
2018-01-01
Karst areas are typical ecologically fragile areas, and stony desertification has become the most serious ecological and economic problems in these areas worldwide as well as a source of disasters and poverty. A reasonable sampling scale is of great importance for research on soil science in karst areas. In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in karst areas are studied at different sampling scales using a grid sampling method based on geographic information system (GIS) technology and geo-statistics. The rock exposure obtained through sampling over a 150 m × 150 m grid in the Houzhai River Basin was utilized as the original data, and five grid scales (300 m × 300 m, 450 m × 450 m, 600 m × 600 m, 750 m × 750 m, and 900 m × 900 m) were used as the subsample sets. The results show that the rock exposure does not vary substantially from one sampling scale to another, while the average values of the five subsamples all fluctuate around the average value of the entire set. As the sampling scale increases, the maximum value and the average value of the rock exposure gradually decrease, and there is a gradual increase in the coefficient of variability. At the scale of 150 m × 150 m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km2, 4.50 km2, and 1.87 km2, respectively. The spatial variability of stony desertification at small scales is influenced by many factors, and the variability at medium scales is jointly influenced by gradient, rock content, and rock exposure. At large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock content. PMID:29652811
Zhang, Zhenming; Zhou, Yunchao; Wang, Shijie; Huang, Xianfei
2018-04-13
Karst areas are typical ecologically fragile areas, and stony desertification has become the most serious ecological and economic problems in these areas worldwide as well as a source of disasters and poverty. A reasonable sampling scale is of great importance for research on soil science in karst areas. In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in karst areas are studied at different sampling scales using a grid sampling method based on geographic information system (GIS) technology and geo-statistics. The rock exposure obtained through sampling over a 150 m × 150 m grid in the Houzhai River Basin was utilized as the original data, and five grid scales (300 m × 300 m, 450 m × 450 m, 600 m × 600 m, 750 m × 750 m, and 900 m × 900 m) were used as the subsample sets. The results show that the rock exposure does not vary substantially from one sampling scale to another, while the average values of the five subsamples all fluctuate around the average value of the entire set. As the sampling scale increases, the maximum value and the average value of the rock exposure gradually decrease, and there is a gradual increase in the coefficient of variability. At the scale of 150 m × 150 m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km², 4.50 km², and 1.87 km², respectively. The spatial variability of stony desertification at small scales is influenced by many factors, and the variability at medium scales is jointly influenced by gradient, rock content, and rock exposure. At large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock content.
Grech, Alana; Sheppard, James; Marsh, Helene
2011-01-01
Background Conservation planning and the design of marine protected areas (MPAs) requires spatially explicit information on the distribution of ecological features. Most species of marine mammals range over large areas and across multiple planning regions. The spatial distributions of marine mammals are difficult to predict using habitat modelling at ecological scales because of insufficient understanding of their habitat needs, however, relevant information may be available from surveys conducted to inform mandatory stock assessments. Methodology and Results We use a 20-year time series of systematic aerial surveys of dugong (Dugong dugong) abundance to create spatially-explicit models of dugong distribution and relative density at the scale of the coastal waters of northeast Australia (∼136,000 km2). We interpolated the corrected data at the scale of 2 km * 2 km planning units using geostatistics. Planning units were classified as low, medium, high and very high dugong density on the basis of the relative density of dugongs estimated from the models and a frequency analysis. Torres Strait was identified as the most significant dugong habitat in northeast Australia and the most globally significant habitat known for any member of the Order Sirenia. The models are used by local, State and Federal agencies to inform management decisions related to the Indigenous harvest of dugongs, gill-net fisheries and Australia's National Representative System of Marine Protected Areas. Conclusion/Significance In this paper we demonstrate that spatially-explicit population models add value to data collected for stock assessments, provide a robust alternative to predictive habitat distribution models, and inform species conservation at multiple scales. PMID:21464933
Shi, Yu; Li, Yuntao; Xiang, Xingjia; Sun, Ruibo; Yang, Teng; He, Dan; Zhang, Kaoping; Ni, Yingying; Zhu, Yong-Guan; Adams, Jonathan M; Chu, Haiyan
2018-02-05
The relative importance of stochasticity versus determinism in soil bacterial communities is unclear, as are the possible influences that alter the balance between these. Here, we investigated the influence of spatial scale on the relative role of stochasticity and determinism in agricultural monocultures consisting only of wheat, thereby minimizing the influence of differences in plant species cover and in cultivation/disturbance regime, extending across a wide range of soils and climates of the North China Plain (NCP). We sampled 243 sites across 1092 km and sequenced the 16S rRNA bacterial gene using MiSeq. We hypothesized that determinism would play a relatively stronger role at the broadest scales, due to the strong influence of climate and soil differences in selecting many distinct OTUs of bacteria adapted to the different environments. In order to test the more general applicability of the hypothesis, we also compared with a natural ecosystem on the Tibetan Plateau. Our results revealed that the relative importance of stochasticity vs. determinism did vary with spatial scale, in the direction predicted. On the North China Plain, stochasticity played a dominant role from 150 to 900 km (separation between pairs of sites) and determinism dominated at more than 900 km (broad scale). On the Tibetan Plateau, determinism played a dominant role from 130 to 1200 km and stochasticity dominated at less than 130 km. Among the identifiable deterministic factors, soil pH showed the strongest influence on soil bacterial community structure and diversity across the North China Plain. Together, 23.9% of variation in soil microbial community composition could be explained, with environmental factors accounting for 19.7% and spatial parameters 4.1%. Our findings revealed that (1) stochastic processes are relatively more important on the North China Plain, while deterministic processes are more important on the Tibetan Plateau; (2) soil pH was the major factor in shaping soil bacterial community structure of the North China Plain; and (3) most variation in soil microbial community composition could not be explained with existing environmental and spatial factors. Further studies are needed to dissect the influence of stochastic factors (e.g., mutations or extinctions) on soil microbial community distribution, which might make it easier to predictably manipulate the microbial community to produce better yield and soil sustainability outcomes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mishra, U.; Riley, W. J.
The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less
NASA Astrophysics Data System (ADS)
Xu, C.; Zhao, S.; Zhao, B.
2017-12-01
Spatial heterogeneity is scale-dependent, that is, the quantification and representation of spatial pattern vary with the resolution and extent. Overwhelming practices focused on scale effect of landscape metrics, and predicable scaling relationships found among some of them are thought to be the most effective and precise way to quantify multi-scale characteristics. However, previous studies tended to consider a narrow range of scales, and few focused on the critical threshold of scaling function. Here we examine the scalograms of 38 widely-used landscape-level metrics in a more integral spectrum of grain size among 96 landscapes with various extent (i.e. from 25km2 up towards to 221 km2), which sampled randomly from NLCD product. Our goal is to explore the existence of scaling domain and whether the response of metrics to changing resolution would be influenced by spatial extent. Results clearly show the existence of scaling domain for 13 of them (Type II), while the behaviors of other 13 (Type I) exhibit simple scaling functions and the rest (Type III) demonstrate various forms like no obvious change or fluctuation across the integral spectrum of grain size. In addition, an invariant power law scaling relationship was found between critical resolution and spatial extent for metrics falling into Type II, as the critical resolution is proportional to Eρ (ρ is a constant, and E is the extent). All the scaling exponents (ρ) are positive, suggesting that the critical resolutions for these characteristics of landscape structure can be relaxed as the spatial extent expands. This agrees well with empirical perception that coarser grain size might be allowed for spatial data with larger extent. Furthermore, the parameters of scaling functions for metrics falling into Type I and Type II vary with spatial extent, and power law or logarithmic relationships could be identified between them for some metrics. Our finding support the existence of self-organized criticality for a hierarchically-structured landscape. Although the underlying mechanism driving the scaling relationship remains unclear, it could provide guidance toward general principles in spatial pattern analysis and on selecting the proper resolution to avoid the misrepresentation of spatial pattern and profound biases in further ecological progress research.
MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region
NASA Technical Reports Server (NTRS)
Munchak, L. A.; Levy, R. C.; Mattoo, S.; Remer, L. A.; Holben, B. N.; Schafer, J. S.; Hostetler, C. A.; Ferrare, R. A.
2013-01-01
MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.
NASA Astrophysics Data System (ADS)
Pérez-Ruzafa, A.; Marcos, C.; Pérez-Ruzafa, I. M.; Barcala, E.; Hegazi, M. I.; Quispe, J.
2007-10-01
To detect changes in ecosystems due to human impact, experimental designs must include replicates at the appropriate scale to avoid pseudoreplication. Although coastal lagoons, with their highly variable environmental factors and biological assemblages, are relatively well-studied systems, very little is known about their natural scales of variation. In this study, we investigate the spatio-temporal scales of variability in the Mar Menor coastal lagoon (SE Spain) using structured hierarchical sampling designs, mixed and permutational multi-variate analyses of variance, and ordination multi-variate analyses applied to hydrographical parameters, nutrients, chlorophyll a and ichthyoplankton in the water column, and to macrophyte and fish benthic assemblages. Lagoon processes in the Mar Menor show heterogeneous patterns at different temporal and spatial scales. The water column characteristics (including nutrient concentration) showed small-scale spatio-temporal variability, from 10 0 to 10 1 km and from fortnightly to seasonally. Biological features (chlorophyll a concentration and ichthyoplankton assemblage descriptors) showed monthly changes and spatial patterns at the scale of 10 0 (chlorophyll a) - 10 1 km (ichthyoplankton). Benthic assemblages (macrophytes and fishes) showed significant differences between types of substrates in the same locality and between localities, according to horizontal gradients related with confinement in the lagoon, at the scale of 10 0-10 1 km. The vertical zonation of macrophyte assemblages (at scales of 10 1-10 2 cm) overlaps changes in substrata and horizontal gradients. Seasonal patterns in vegetation biomass were not significant, but the significant interaction between Locality and Season indicated that the seasons of maximum and minimum biomass depend on local environmental conditions. Benthic fish assemblages showed no significant patterns at the monthly scale but did show seasonal patterns.
Comprehensive geo-spatial data creation for Najran region in the KSA
NASA Astrophysics Data System (ADS)
Alrajhi, M.; Hawarey, M.
2009-04-01
The General Directorate for Surveying and Mapping (GDSM) of the Deputy Ministry for Land and Surveying (DMLS) of the Ministry of Municipal and Rural Affairs (MOMRA) in the Kingdom of Saudi Arabia (KSA) has the exclusive mandate to carry out aerial photography and produce large-scale detailed maps for about 220 cities and villages in the KSA. This presentation is about the comprehensive geo-spatial data creation for the Najran region, South KSA, that was founded on country-wide horizontal geodetic ground control using Global Navigation Satellite Systems (GNSS) within the MOMRA's Terrestrial Reference Frame 2000 (MTRF2000) that is tied to International Terrestrial Reference Frame 2000 (ITRF2000) Epoch 2004.0, and vertical geodetic ground control using precise digital leveling in reference to Jeddah 1969 mean sea level, and included aerial photography of area 917 km2 at 1:5,500 scale and 14,304 km2 at 1:45,000 scale, full aerial triangulation, and production of orthophoto maps at scale of 1:10,000 (298 sheets) for 14,304 km2, with aerial photography lasting from May 2006 until July 2006.
Comprehensive geo-spatial data creation for Ar-Riyadh region in the KSA
NASA Astrophysics Data System (ADS)
Alrajhi, M.; Hawarey, M.
2009-04-01
The General Directorate for Surveying and Mapping (GDSM) of the Deputy Ministry for Land and Surveying (DMLS) of the Ministry of Municipal and Rural Affairs (MOMRA) in the Kingdom of Saudi Arabia (KSA) has the exclusive mandate to carry out aerial photography and produce large-scale detailed maps for about 220 cities and villages in the KSA. This presentation is about the comprehensive geo-spatial data creation for the Ar-Riyadh region, Central KSA, that was founded on country-wide horizontal geodetic ground control using Global Navigation Satellite Systems (GNSS) within the MOMRA's Terrestrial Reference Frame 2000 (MTRF2000) that is tied to International Terrestrial Reference Frame 2000 (ITRF2000) Epoch 2004.0, and vertical geodetic ground control using precise digital leveling in reference to Jeddah 1969 mean sea level, and included aerial photography of area 3,000 km2 at 1:5,500 scale and 10,000 km2 at 1:45,000 scale, full aerial triangulation, and production of orthophoto maps at scale of 1:10,000 (480 sheets) for 10,000 km2, with aerial photography lasting from July 2007 thru August 2007.
Small-Scale Dynamical Structures Using OH Airglow From Astronomical Observations
NASA Astrophysics Data System (ADS)
Franzen, C.; Espy, P. J.; Hibbins, R. E.; Djupvik, A. A.
2017-12-01
Remote sensing of perturbations in the hydroxyl (OH) Meinel airglow has often been used to observe gravity, tidal and planetary waves travelling through the 80-90 km region. While large scale (>1 km) gravity waves and the winds caused by their breaking are widely documented, information on the highest frequency waves and instabilities occurring during the breaking process is often limited by the temporal and spatial resolution of the available observations. In an effort to better quantify the full range of wave scales present near the mesopause, we present a series of observations of the OH Meinel (9,7) transition that were executed with the Nordic Optical Telescope on La Palma (18°W, 29°N). These measurements have a 24 s repetition rate and horizontal spatial resolutions at 87 km as small as 10 cm, allowing us to quantify the transition in the mesospheric wave domains as the gravity waves break. Temporal scales from hours to minutes, as well as sub-100 m coherent structures in the OH airglow have been observed and will be presented.
Comprehensive geo-spatial data creation for Asir region in the KSA
NASA Astrophysics Data System (ADS)
Alrajhi, M.; Hawarey, M.
2009-04-01
The General Directorate for Surveying and Mapping (GDSM) of the Deputy Ministry for Land and Surveying (DMLS) of the Ministry of Municipal and Rural Affairs (MOMRA) in the Kingdom of Saudi Arabia (KSA) has the exclusive mandate to carry out aerial photography and produce large-scale detailed maps for about 220 cities and villages in the KSA. This presentation is about the comprehensive geo-spatial data creation for the Asir region, South West KSA, that was founded on country-wide horizontal geodetic ground control using Global Navigation Satellite Systems (GNSS) within the MOMRA's Terrestrial Reference Frame 2000 (MTRF2000) that is tied to International Terrestrial Reference Frame 2000 (ITRF2000) Epoch 2004.0, and vertical geodetic ground control using precise digital leveling in reference to Jeddah 1969 mean sea level, and included aerial photography of area 2,188 km2 at 1:5,500 scale and 32,640 km2 at 1:45,000 scale, full aerial triangulation, and production of orthophoto maps at scale of 1:10,000 (680 sheets) for 32,640 km2, with aerial photography lasting from July 2007 thru October 2007.
Circulation controls of the spatial structure of maximum daily precipitation over Poland
NASA Astrophysics Data System (ADS)
Stach, Alfred
2015-04-01
Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.
Casas-Güell, Edgar; Cebrian, Emma; Garrabou, Joaquim; Ledoux, Jean-Baptiste; Linares, Cristina; Teixidó, Núria
2016-01-01
Data on species diversity and structure in coralligenous outcrops dominated by Corallium rubrum are lacking. A hierarchical sampling including 3 localities and 9 sites covering more than 400 km of rocky coasts in NW Mediterranean, was designed to characterize the spatial variability of structure, composition and diversity of perennial species inhabiting coralligenous outcrops. We estimated species/taxa composition and abundance. Eight morpho-functional groups were defined according to their life span and growth to characterize the structural complexity of the outcrops. The species composition and structural complexity differed consistently across all spatial scales considered. The lowest and the highest variability were found among localities (separated by >200 km) and within sites (separated by 1–5 km), respectively supporting differences in diversity indices. The morpho-functional groups displayed a consistent spatial arrangement in terms of the number, size and shape of patches across study sites. These results contribute to filling the gap on the understanding of assemblage composition and structure and to build baselines to assess the response of this of this highly threatened habitat to anthropogenic disturbances. PMID:27857209
Effects of spatial variability and scale on areal -average evapotranspiration
NASA Technical Reports Server (NTRS)
Famiglietti, J. S.; Wood, Eric F.
1993-01-01
This paper explores the effect of spatial variability and scale on areally-averaged evapotranspiration. A spatially-distributed water and energy balance model is employed to determine the effect of explicit patterns of model parameters and atmospheric forcing on modeled areally-averaged evapotranspiration over a range of increasing spatial scales. The analysis is performed from the local scale to the catchment scale. The study area is King's Creek catchment, an 11.7 sq km watershed located on the native tallgrass prairie of Kansas. The dominant controls on the scaling behavior of catchment-average evapotranspiration are investigated by simulation, as is the existence of a threshold scale for evapotranspiration modeling, with implications for explicit versus statistical representation of important process controls. It appears that some of our findings are fairly general, and will therefore provide a framework for understanding the scaling behavior of areally-averaged evapotranspiration at the catchment and larger scales.
López-Bao, José V.; González-Varo, Juan P.
2011-01-01
Background Knowledge about how frugivory and seed deposition are spatially distributed is valuable to understand the role of dispersers on the structure and dynamics of plant populations. This may be particularly important within anthropogenic areas, where either the patchy distribution of wild plants or the presence of cultivated fleshy-fruits may influence plant-disperser interactions. Methodology/Principal Findings We investigated frugivory and spatial patterns of seed deposition by carnivorous mammals in anthropogenic landscapes considering two spatial scales: ‘landscape’ (∼10 km2) and ‘habitat type’ (∼1–2 km2). We sampled carnivore faeces and plant abundance at three contrasting habitats (chestnut woods, mosaics and scrublands), each replicated within three different landscapes. Sixty-five percent of faeces collected (n = 1077) contained seeds, among which wild and cultivated seeds appeared in similar proportions (58% and 53%) despite that cultivated fruiting plants were much less abundant. Seed deposition was spatially structured among both spatial scales being different between fruit types. Whereas the most important source of spatial variation in deposition of wild seeds was the landscape scale, it was the habitat scale for cultivated seeds. At the habitat scale, seeds of wild species were mostly deposited within mosaics while seeds of cultivated species were within chestnut woods and scrublands. Spatial concordance between seed deposition and plant abundance was found only for wild species. Conclusions/Significance Spatial patterns of seed deposition by carnivores differed between fruit types and seemed to be modulated by the fleshy-fruited plant assemblages and the behaviour of dispersers. Our results suggest that a strong preference for cultivated fruits by carnivores may influence their spatial foraging behaviour and lower their dispersal services to wild species. However, the high amount of seeds removed within and between habitats suggests that carnivores must play an important role – often overlooked – as ‘restorers’ and ‘habitat shapers’ in anthropogenic areas. PMID:21297861
NASA Astrophysics Data System (ADS)
Shi, X.; Zhao, C.
2017-12-01
Haze aerosol pollution has been a focus issue in China, and its characteristics is highly demanded. With limited observation sites, aerosol properties obtained from a single site is frequently used to represent the haze condition over a large domain, such as tens of kilometers. This could result in high uncertainties in the haze characteristics due to their spatial variation. Using a network observation from November 2015 to February 2016 over an urban city in North China with high spatial resolution, this study examines the spatial representation of ground site observations. A method is first developed to determine the representative area of measurements from limited stations. The key idea of this method is to determine the spatial variability of particulate matter with diameters less than 2.5 μm (PM2.5) concentration using a variance function in 2km x 2km grids. Based on the high spatial resolution (0.5km x 0.5km) measurements of PM2.5, the grids in which PM2.5 have high correlations and weak value differences are determined as the representation area of measurements at these grids. Note that the size representation area is not exactly a circle region. It shows that the size representation are for the study region and study period ranges from 0.25 km2 to 16.25 km2. The representation area varies with locations. For the 20 km x 20 km study region, 10 station observations would have a good representation of the PM2.5 observations obtained from current 169 stations at the four-month time scale.
Hybrid modeling of spatial continuity for application to numerical inverse problems
Friedel, Michael J.; Iwashita, Fabio
2013-01-01
A novel two-step modeling approach is presented to obtain optimal starting values and geostatistical constraints for numerical inverse problems otherwise characterized by spatially-limited field data. First, a type of unsupervised neural network, called the self-organizing map (SOM), is trained to recognize nonlinear relations among environmental variables (covariates) occurring at various scales. The values of these variables are then estimated at random locations across the model domain by iterative minimization of SOM topographic error vectors. Cross-validation is used to ensure unbiasedness and compute prediction uncertainty for select subsets of the data. Second, analytical functions are fit to experimental variograms derived from original plus resampled SOM estimates producing model variograms. Sequential Gaussian simulation is used to evaluate spatial uncertainty associated with the analytical functions and probable range for constraining variables. The hybrid modeling of spatial continuity is demonstrated using spatially-limited hydrologic measurements at different scales in Brazil: (1) physical soil properties (sand, silt, clay, hydraulic conductivity) in the 42 km2 Vargem de Caldas basin; (2) well yield and electrical conductivity of groundwater in the 132 km2 fractured crystalline aquifer; and (3) specific capacity, hydraulic head, and major ions in a 100,000 km2 transboundary fractured-basalt aquifer. These results illustrate the benefits of exploiting nonlinear relations among sparse and disparate data sets for modeling spatial continuity, but the actual application of these spatial data to improve numerical inverse modeling requires testing.
Ernesto Trujillo; Jorge A. Ramirez; Kelly J. Elder
2007-01-01
In this study, LIDAR snow depths, bare ground elevations (topography), and elevations filtered to the top of vegetation (topography + vegetation) in five 1-km2 areas are used to determine whether the spatial distribution of snow depth exhibits scale invariance, and the control that vegetation, topography, and winds exert on such behavior. The one-dimensional and mean...
NASA Astrophysics Data System (ADS)
Turner, Alexander J.; Jacob, Daniel J.; Benmergui, Joshua; Brandman, Jeremy; White, Laurent; Randles, Cynthia A.
2018-06-01
Anthropogenic methane emissions originate from a large number of fine-scale and often transient point sources. Satellite observations of atmospheric methane columns are an attractive approach for monitoring these emissions but have limitations from instrument precision, pixel resolution, and measurement frequency. Dense observations will soon be available in both low-Earth and geostationary orbits, but the extent to which they can provide fine-scale information on methane sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) to assess the capabilities of different satellite observing system configurations. We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 × 1.3 km2 spatial resolution and hourly temporal resolution over a 290 × 235 km2 domain in the Barnett Shale, a major oil and gas field in Texas with a large number of point sources. We sub-sample these footprints to match the observing characteristics of the recently launched TROPOMI instrument (7 × 7 km2 pixels, 11 ppb precision, daily frequency), the planned GeoCARB instrument (2.7 × 3.0 km2 pixels, 4 ppb precision, nominal twice-daily frequency), and other proposed observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its eigenvalues. We find that a week of TROPOMI observations should provide information on temporally invariant emissions at ˜ 30 km spatial resolution. GeoCARB should provide information available on temporally invariant emissions ˜ 2-7 km spatial resolution depending on sampling frequency (hourly to daily). Improvements to the instrument precision yield greater increases in information content than improved sampling frequency. A precision better than 6 ppb is critical for GeoCARB to achieve fine resolution of emissions. Transient emissions would be missed with either TROPOMI or GeoCARB. An aspirational high-resolution geostationary instrument with 1.3 × 1.3 km2 pixel resolution, hourly return time, and 1 ppb precision would effectively constrain the temporally invariant emissions in the Barnett Shale at the kilometer scale and provide some information on hourly variability of sources.
Large-scale modeling of rain fields from a rain cell deterministic model
NASA Astrophysics Data System (ADS)
FéRal, Laurent; Sauvageot, Henri; Castanet, Laurent; Lemorton, JoëL.; Cornet, FréDéRic; Leconte, Katia
2006-04-01
A methodology to simulate two-dimensional rain rate fields at large scale (1000 × 1000 km2, the scale of a satellite telecommunication beam or a terrestrial fixed broadband wireless access network) is proposed. It relies on a rain rate field cellular decomposition. At small scale (˜20 × 20 km2), the rain field is split up into its macroscopic components, the rain cells, described by the Hybrid Cell (HYCELL) cellular model. At midscale (˜150 × 150 km2), the rain field results from the conglomeration of rain cells modeled by HYCELL. To account for the rain cell spatial distribution at midscale, the latter is modeled by a doubly aggregative isotropic random walk, the optimal parameterization of which is derived from radar observations at midscale. The extension of the simulation area from the midscale to the large scale (1000 × 1000 km2) requires the modeling of the weather frontal area. The latter is first modeled by a Gaussian field with anisotropic covariance function. The Gaussian field is then turned into a binary field, giving the large-scale locations over which it is raining. This transformation requires the definition of the rain occupation rate over large-scale areas. Its probability distribution is determined from observations by the French operational radar network ARAMIS. The coupling with the rain field modeling at midscale is immediate whenever the large-scale field is split up into midscale subareas. The rain field thus generated accounts for the local CDF at each point, defining a structure spatially correlated at small scale, midscale, and large scale. It is then suggested that this approach be used by system designers to evaluate diversity gain, terrestrial path attenuation, or slant path attenuation for different azimuth and elevation angle directions.
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.
NASA Astrophysics Data System (ADS)
Matsui, H.; Koike, M.; Kondo, Y.; Takegawa, N.; Kita, K.; Miyazaki, Y.; Hu, M.; Chang, S.; Blake, D. R.; Fast, J. D.; Zaveri, R. A.; Streets, D. G.; Zhang, Q.; Zhu, T.
2009-12-01
Regional aerosol model calculations were made using the WRF-CMAQ and WRF-chem models to study spatial and temporal variations of aerosols around Beijing, China, in the summer of 2006, when the CAREBEIJING-2006 intensive campaign was conducted. Model calculations captured temporal variations of primary (such as elemental carbon, EC) and secondary (such as sulfate) aerosols observed in and around Beijing. The spatial distributions of aerosol optical depth observed by the MODIS satellite sensors were also reproduced over northeast China. Model calculations showed distinct differences in spatial distributions between primary and secondary aerosols in association with synoptic-scale meteorology. Secondary aerosols increased in air around Beijing on a scale of about 1000 x 1000 km2 under an anticyclonic pressure system. This airmass was transported northward from the high anthropogenic emission area extending south of Beijing with continuous photochemical production. Subsequent cold front passage brought clean air from the north, and polluted air around Beijing was swept to the south of Beijing. This cycle was repeated about once a week and was found to be responsible for observed enhancements/reductions of aerosols at the intensive measurement sites. In contrast to secondary aerosols, the spatial distributions of primary aerosols (EC) reflected those of emissions, resulting in only slight variability despite the changes in synoptic-scale meteorology. In accordance with these results, source apportionment simulations revealed that primary aerosols around Beijing were controlled by emissions within 100 km around Beijing within the preceding 24 hours, while emissions as far as 500 km and within the preceding 3 days were found to affect secondary aerosols.
SST Variation Due to Interactive Convective-Radiative Processes
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Shie, C.-L.; Johnson, D.; Simpson, J.; Li, X.; Sui, C.-H.
2000-01-01
The recent linking of Cloud-Resolving Models (CRMs) to Ocean-Mixed Layer (OML) models has provided a powerful new means of quantifying the role of cloud systems in ocean-atmosphere coupling. This is due to the fact that the CRM can better resolve clouds and cloud systems and allow for explicit cloud-radiation interaction. For example, Anderson (1997) applied an atmospheric forcing associated with a CRM simulated squall line to a 3-D OML model (one way or passive interaction). His results suggested that the spatial variability resulting from the squall forcing can last at least 24 hours when forced with otherwise spatially uniform fluxes. In addition, the sea surface salinity (SSS) variability continuously decreased following the forcing, while some of the SST variability remained when a diurnal mixed layer capped off the surface structure. The forcing used in the OML model, however, focused on shorter time (8 h) and smaller spatial scales (100-120 km). In this study, the 3-D Goddard Cumulus Ensemble Model (GCE; 512 x 512 x 23 cu km, 2-km horizontal resolution) is used to simulate convective active episodes occurring in the Western Pacific warm pool and Eastern Atlantic regions. The model is integrated for seven days, and the simulated results are coupled to an OML model to better understand the impact of precipitation and changes in the planetary boundary layer upon SST variation. We will specifically examine and compare the results of linking the OML model with various spatially-averaged outputs from GCE simulations (i.e., 2 km vs. 10-50 km horizontal resolutions), in order to help understand the SST sensitivity to multi-scale influences. This will allow us to assess the importance of explicitly simulated deep and shallow clouds, as well as the subgrid-scale effects (in coarse-model runs) upon SST variation. Results using both 1-D and 2-D OML models will be evaluated to assess the effects of horizontal advection.
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.
Testing scale-dependent effects of seminatural habitats on farmland biodiversity.
Dainese, Matteo; Luna, Diego Inclán; Sitzia, Tommaso; Marini, Lorenzo
2015-09-01
The effectiveness of conservation interventions for maximizing biodiversity benefits from agri-environment schemes (AESs) is expected to depend on the quantity of seminatural habitats in the surrounding landscape. To verify this hypothesis, we developed a hierarchical sampling design to assess the effects of field boundary type and cover of seminatural habitats in the landscape at two nested spatial scales. We sampled three types of field boundaries with increasing structural complexity (grass margin, simple hedgerow, complex hedgerow) in paired landscapes with the presence or absence of seminatural habitats (radius 0.5 km), that in turn, were nested within 15 areas with different proportions of seminatural habitats at a larger spatial scale (10 X 10 km). Overall, 90 field boundaries were sampled across a Mediterranean'region (northeastern Italy). We considered species richness response across three different taxonomic groups: vascular plants, butterflies, and tachinid flies. No interactions between type of field boundary and surrounding landscape were found at either 0.5 and 10 km, indicating that the quality of field boundary had the same effect irrespective of the cover of seminatural habitats. At the local scale, extended-width grass margins yielded higher plant species richness, while hedgerows yielded higher species richness of butterflies and tachinids. At the 0.5-km landscape scale, the effect of the proportion of seminatural habitats was neutral for plants and tachinids, while butterflies were positively related to the proportion of forest. At the 10-km landscape scale, only butterflies responded positively to the proportion of seminatural habitats. Our study confirmed the importance of testing multiple scales when considering species from different taxa and with different mobility. We showed that the quality of field boundaries at the local scale was an important factor in enhancing farmland biodiversity. For butterflies, AESs should focus particular attention on preservation'of forest patches in agricultural landscapes within 0.5 kin, as well as the conservation of seminatural habitats at a wider landscape scale.
Land-Atmosphere Coupling in the Multi-Scale Modelling Framework
NASA Astrophysics Data System (ADS)
Kraus, P. M.; Denning, S.
2015-12-01
The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced conceptual gap between model resolution and parameterized processes.
Field Scale Spatial Modelling of Surface Soil Quality Attributes in Controlled Traffic Farming
NASA Astrophysics Data System (ADS)
Guenette, Kris; Hernandez-Ramirez, Guillermo
2017-04-01
The employment of controlled traffic farming (CTF) can yield improvements to soil quality attributes through the confinement of equipment traffic to tramlines with the field. There is a need to quantify and explain the spatial heterogeneity of soil quality attributes affected by CTF to further improve our understanding and modelling ability of field scale soil dynamics. Soil properties such as available nitrogen (AN), pH, soil total nitrogen (STN), soil organic carbon (SOC), bulk density, macroporosity, soil quality S-Index, plant available water capacity (PAWC) and unsaturated hydraulic conductivity (Km) were analysed and compared among trafficked and un-trafficked areas. We contrasted standard geostatistical methods such as ordinary kriging (OK) and covariate kriging (COK) as well as the hybrid method of regression kriging (ROK) to predict the spatial distribution of soil properties across two annual cropland sites actively employing CTF in Alberta, Canada. Field scale variability was quantified more accurately through the inclusion of covariates; however, the use of ROK was shown to improve model accuracy despite the regression model composition limiting the robustness of the ROK method. The exclusion of traffic from the un-trafficked areas displayed significant improvements to bulk density, macroporosity and Km while subsequently enhancing AN, STN and SOC. The ability of the regression models and the ROK method to account for spatial trends led to the highest goodness-of-fit and lowest error achieved for the soil physical properties, as the rigid traffic regime of CTF altered their spatial distribution at the field scale. Conversely, the COK method produced the most optimal predictions for the soil nutrient properties and Km. The use of terrain covariates derived from light ranging and detection (LiDAR), such as of elevation and topographic position index (TPI), yielded the best models in the COK method at the field scale.
Soil nutrients influence spatial distributions of tropical tree species.
John, Robert; Dalling, James W; Harms, Kyle E; Yavitt, Joseph B; Stallard, Robert F; Mirabello, Matthew; Hubbell, Stephen P; Valencia, Renato; Navarrete, Hugo; Vallejo, Martha; Foster, Robin B
2007-01-16
The importance of niche vs. neutral assembly mechanisms in structuring tropical tree communities remains an important unsettled question in community ecology [Bell G (2005) Ecology 86:1757-1770]. There is ample evidence that species distributions are determined by soils and habitat factors at landscape (<10(4) km(2)) and regional scales. At local scales (<1 km(2)), however, habitat factors and species distributions show comparable spatial aggregation, making it difficult to disentangle the importance of niche and dispersal processes. In this article, we test soil resource-based niche assembly at a local scale, using species and soil nutrient distributions obtained at high spatial resolution in three diverse neotropical forest plots in Colombia (La Planada), Ecuador (Yasuni), and Panama (Barro Colorado Island). Using spatial distribution maps of >0.5 million individual trees of 1,400 species and 10 essential plant nutrients, we used Monte Carlo simulations of species distributions to test plant-soil associations against null expectations based on dispersal assembly. We found that the spatial distributions of 36-51% of tree species at these sites show strong associations to soil nutrient distributions. Neutral dispersal assembly cannot account for these plant-soil associations or the observed niche breadths of these species. These results indicate that belowground resource availability plays an important role in the assembly of tropical tree communities at local scales and provide the basis for future investigations on the mechanisms of resource competition among tropical tree species.
2010-01-01
Background The population genetic structure of subterranean rodent species is strongly affected by demographic (e.g. rates of dispersal and social structure) and stochastic factors (e.g. random genetic drift among subpopulations and habitat fragmentation). In particular, gene flow estimates at different spatial scales are essential to understand genetic differentiation among populations of a species living in a highly fragmented landscape. Ctenomys australis (the sand dune tuco-tuco) is a territorial subterranean rodent that inhabits a relatively secure, permanently sealed burrow system, occurring in sand dune habitats on the coastal landscape in the south-east of Buenos Aires province, Argentina. Currently, this habitat is threatened by urban development and forestry and, therefore, the survival of this endemic species is at risk. Here, we assess population genetic structure and patterns of dispersal among individuals of this species at different spatial scales using 8 polymorphic microsatellite loci. Furthermore, we evaluate the relative importance of sex and habitat configuration in modulating the dispersal patterns at these geographical scales. Results Our results show that dispersal in C. australis is not restricted at regional spatial scales (~ 4 km). Assignment tests revealed significant population substructure within the study area, providing support for the presence of two subpopulations from three original sampling sites. Finally, male-biased dispersal was found in the Western side of our study area, but in the Eastern side no apparent philopatric pattern was found, suggesting that in a more continuous habitat males might move longer distances than females. Conclusions Overall, the assignment-based approaches were able to detect population substructure at fine geographical scales. Additionally, the maintenance of a significant genetic structure at regional (~ 4 km) and small (less than 1 km) spatial scales despite apparently moderate to high levels of gene flow between local sampling sites could not be explained simply by the linear distance among them. On the whole, our results support the hypothesis that males disperse more frequently than females; however they do not provide support for strict philopatry within females. PMID:20109219
Variability of the raindrop size distribution at small spatial scales
NASA Astrophysics Data System (ADS)
Berne, A.; Jaffrain, J.
2010-12-01
Because of the interactions between atmospheric turbulence and cloud microphysics, the raindrop size distribution (DSD) is strongly variable in space and time. The spatial variability of the DSD at small spatial scales (below a few km) is not well documented and not well understood, mainly because of a lack of adequate measurements at the appropriate resolutions. A network of 16 disdrometers (Parsivels) has been designed and set up over EPFL campus in Lausanne, Switzerland. This network covers a typical operational weather radar pixel of 1x1 km2. The question of the significance of the variability of the DSD at such small scales is relevant for radar remote sensing of rainfall because the DSD is often assumed to be uniform within a radar sample volume and because the Z-R relationships used to convert the measured radar reflectivity Z into rain rate R are usually derived from point measurements. Thanks to the number of disdrometers, it was possible to quantify the spatial variability of the DSD at the radar pixel scale and to show that it can be significant. In this contribution, we show that the variability of the total drop concentration, of the median volume diameter and of the rain rate are significant, taking into account the sampling uncertainty associated with disdrometer measurements. The influence of this variability on the Z-R relationship can be non-negligible. Finally, the spatial structure of the DSD is quantified using a geostatistical tool, the variogram, and indicates high spatial correlation within a radar pixel.
Cooke, Georgina M; Schlub, Timothy E; Sherwin, William B; Ord, Terry J
2016-01-01
Quantifying the spatial scale of population connectivity is important for understanding the evolutionary potential of ecologically divergent populations and for designing conservation strategies to preserve those populations. For marine organisms like fish, the spatial scale of connectivity is generally set by a pelagic larval phase. This has complicated past estimates of connectivity because detailed information on larval movements are difficult to obtain. Genetic approaches provide a tractable alternative and have the added benefit of estimating directly the reproductive isolation of populations. In this study, we leveraged empirical estimates of genetic differentiation among populations with simulations and a meta-analysis to provide a general estimate of the spatial scale of genetic connectivity in marine environments. We used neutral genetic markers to first quantify the genetic differentiation of ecologically-isolated adult populations of a land dwelling fish, the Pacific leaping blenny (Alticus arnoldorum), where marine larval dispersal is the only probable means of connectivity among populations. We then compared these estimates to simulations of a range of marine dispersal scenarios and to collated FST and distance data from the literature for marine fish across diverse spatial scales. We found genetic connectivity at sea was extensive among marine populations and in the case of A. arnoldorum, apparently little affected by the presence of ecological barriers. We estimated that ~5000 km (with broad confidence intervals ranging from 810-11,692 km) was the spatial scale at which evolutionarily meaningful barriers to gene flow start to occur at sea, although substantially shorter distances are also possible for some taxa. In general, however, such a large estimate of connectivity has important implications for the evolutionary and conservation potential of many marine fish communities.
Environmental Drivers of the Canadian Arctic Megabenthic Communities
Roy, Virginie; Iken, Katrin; Archambault, Philippe
2014-01-01
Environmental gradients and their influence on benthic community structure vary over different spatial scales; yet, few studies in the Arctic have attempted to study the influence of environmental gradients of differing spatial scales on megabenthic communities across continental-scales. The current project studied for the first time how megabenthic community structure is related to several environmental factors over 2000 km of the Canadian Arctic, from the Beaufort Sea to northern Baffin Bay. Faunal trawl samples were collected between 2007 and 2011 at 78 stations from 30 to 1000 m depth and patterns in biomass, density, richness, diversity, and taxonomic composition were examined in relation to indirect/spatial gradients (e.g., depth), direct gradients (e.g., bottom oceanographic variables), and resource gradients (e.g., food supply proxies). Six benthic community types were defined based on their biomass-based taxonomic composition. Their distribution was significantly, but moderately, associated with large-scale (100–1000 km) environmental gradients defined by depth, physical water properties (e.g., bottom salinity), and meso-scale (10–100 km) environmental gradients defined by substrate type (hard vs. soft) and sediment organic carbon content. We did not observe a strong decline of bulk biomass, density and richness with depth or a strong increase of those community characteristics with food supply proxies, contrary to our hypothesis. We discuss how local- to meso-scale environmental conditions, such as bottom current regimes and polynyas, sustain biomass-rich communities at specific locations in oligotrophic and in deep regions of the Canadian Arctic. This study demonstrates the value of considering the scales of variability of environmental gradients when interpreting their relevance in structuring of communities. PMID:25019385
Yang, Q.; Jung, H.B.; Culbertson, C.W.; Marvinney, R.G.; Loiselle, M.C.; Locke, D.B.; Cheek, H.; Thibodeau, H.; Zheng, Yen
2009-01-01
In New England, groundwater arsenic occurrence has been linked to bedrock geology on regional scales. To ascertain and quantify this linkage at intermediate (100-101 km) scales, 790 groundwater samples from fractured bedrock aquifers in the greater Augusta, Maine area are analyzed, and 31% of the sampled wells have arsenic concentrations >10 ??g/L. The probability of [As] exceeding 10 ??g/L mapped by indicator kriging is highest in Silurian pelite-sandstone and pelite-limestone units (???40%). This probability differs significantly (p < 0.001) from those in the Silurian - Ordovician sandstone (24%), the Devonian granite (15%), and the Ordovician - Cambrian volcanic rocks (9%). The spatial pattern of groundwater arsenic distribution resembles the bedrock map. Thus, bedrock geology is associated with arsenic occurrence in fractured bedrock aquifers of the study area at intermediate scales relevant to water resources planning. The arsenic exceedance rate for each rock unit is considered robust because low, medium, and high arsenic occurrences in four cluster areas (3-20 km2) with a low sampling density of 1-6 wells per km2 are comparable to those with a greater density of 5-42 wells per km2. About 12,000 people (21% of the population) in the greater Augusta area (???1135 km2) are at risk of exposure to >10 ??g/L arsenic in groundwater. ?? 2009 American Chemical Society.
Yang, Qiang; Jung, Hun Bok; Culbertson, Charles W.; Marvinney, Robert G.; Loiselle, Marc C.; Locke, Daniel B.; Cheek, Heidi; Thibodeau, Hilary; Zheng, Yan
2009-01-01
In New England, groundwater arsenic occurrence has been linked to bedrock geology on regional scales. To ascertain and quantify this linkage at intermediate (100-101 km) scales, 790 groundwater samples from fractured bedrock aquifers in the greater Augusta, Maine area are analyzed. 31% of the sampled wells have arsenic >10 μg/L. The probability of [As] exceeding 10 μg/L mapped by indicator kriging is highest in Silurian pelite-sandstone and pelite-limestone units (~40%). This probability differs significantly (p<0.001) from those in the Silurian-Ordovician sandstone (24%), the Devonian granite (15%) and the Ordovician-Cambrian volcanic rocks (9%). The spatial pattern of groundwater arsenic distribution resembles the bedrock map. Thus, bedrock geology is associated with arsenic occurrence in fractured bedrock aquifers of the study area at intermediate scales relevant to water resources planning. The arsenic exceedance rate for each rock unit is considered robust because low, medium and high arsenic occurrences in 4 cluster areas (3-20 km2) with a low sampling density of 1-6 wells per km2 are comparable to those with a greater density of 5-42 wells per km2. About 12,000 people (21% of the population) in the greater Augusta area (~1135 km2) are at risk of exposure to >10 μg/L arsenic in groundwater. PMID:19475939
Yang, Qiang; Jung, Hun Bok; Culbertson, Charles W; Marvinney, Robert G; Loiselle, Marc C; Locke, Daniel B; Cheek, Heidi; Thibodeau, Hilary; Zheng, Yan
2009-04-15
In New England, groundwater arsenic occurrence has been linked to bedrock geology on regional scales. To ascertain and quantify this linkage at intermediate (10(0)-10(1) km) scales, 790 groundwater samples from fractured bedrock aquifers in the greater Augusta, Maine area are analyzed, and 31% of the sampled wells have arsenic concentrations >10 microg/L. The probability of [As] exceeding 10 microg/L mapped by indicator kriging is highest in Silurian pelite-sandstone and pelite-limestone units (approximately 40%). This probability differs significantly (p < 0.001) from those in the Silurian-Ordovician sandstone (24%),the Devonian granite (15%), and the Ordovician-Cambrian volcanic rocks (9%). The spatial pattern of groundwater arsenic distribution resembles the bedrock map. Thus, bedrock geology is associated with arsenic occurrence in fractured bedrock aquifers of the study area at intermediate scales relevant to water resources planning. The arsenic exceedance rate for each rock unit is considered robust because low, medium, and high arsenic occurrences in four cluster areas (3-20 km2) with a low sampling density of 1-6 wells per km2 are comparable to those with a greater density of 5-42 wells per km2. About 12,000 people (21% of the population) in the greater Augusta area (approximately 1135 km2) are at risk of exposure to >10 microg/L arsenic in groundwater.
Schmidt, Tom L.; Barton, Nicholas H.; Rašić, Gordana; Turley, Andrew P.; Montgomery, Brian L.; Iturbe-Ormaetxe, Inaki; Cook, Peter E.; Ryan, Peter A.; Ritchie, Scott A.; Hoffmann, Ary A.; O’Neill, Scott L.
2017-01-01
Dengue-suppressing Wolbachia strains are promising tools for arbovirus control, particularly as they have the potential to self-spread following local introductions. To test this, we followed the frequency of the transinfected Wolbachia strain wMel through Ae. aegypti in Cairns, Australia, following releases at 3 nonisolated locations within the city in early 2013. Spatial spread was analysed graphically using interpolation and by fitting a statistical model describing the position and width of the wave. For the larger 2 of the 3 releases (covering 0.97 km2 and 0.52 km2), we observed slow but steady spatial spread, at about 100–200 m per year, roughly consistent with theoretical predictions. In contrast, the smallest release (0.11 km2) produced erratic temporal and spatial dynamics, with little evidence of spread after 2 years. This is consistent with the prediction concerning fitness-decreasing Wolbachia transinfections that a minimum release area is needed to achieve stable local establishment and spread in continuous habitats. Our graphical and likelihood analyses produced broadly consistent estimates of wave speed and wave width. Spread at all sites was spatially heterogeneous, suggesting that environmental heterogeneity will affect large-scale Wolbachia transformations of urban mosquito populations. The persistence and spread of Wolbachia in release areas meeting minimum area requirements indicates the promise of successful large-scale population transformation. PMID:28557993
Schmidt, Tom L; Barton, Nicholas H; Rašić, Gordana; Turley, Andrew P; Montgomery, Brian L; Iturbe-Ormaetxe, Inaki; Cook, Peter E; Ryan, Peter A; Ritchie, Scott A; Hoffmann, Ary A; O'Neill, Scott L; Turelli, Michael
2017-05-01
Dengue-suppressing Wolbachia strains are promising tools for arbovirus control, particularly as they have the potential to self-spread following local introductions. To test this, we followed the frequency of the transinfected Wolbachia strain wMel through Ae. aegypti in Cairns, Australia, following releases at 3 nonisolated locations within the city in early 2013. Spatial spread was analysed graphically using interpolation and by fitting a statistical model describing the position and width of the wave. For the larger 2 of the 3 releases (covering 0.97 km2 and 0.52 km2), we observed slow but steady spatial spread, at about 100-200 m per year, roughly consistent with theoretical predictions. In contrast, the smallest release (0.11 km2) produced erratic temporal and spatial dynamics, with little evidence of spread after 2 years. This is consistent with the prediction concerning fitness-decreasing Wolbachia transinfections that a minimum release area is needed to achieve stable local establishment and spread in continuous habitats. Our graphical and likelihood analyses produced broadly consistent estimates of wave speed and wave width. Spread at all sites was spatially heterogeneous, suggesting that environmental heterogeneity will affect large-scale Wolbachia transformations of urban mosquito populations. The persistence and spread of Wolbachia in release areas meeting minimum area requirements indicates the promise of successful large-scale population transformation.
NASA Astrophysics Data System (ADS)
Longuevergne, Laurent; Scanlon, Bridget R.; Wilson, Clark R.
2010-11-01
The Gravity Recovery and Climate Experiment (GRACE) satellites provide observations of water storage variation at regional scales. However, when focusing on a region of interest, limited spatial resolution and noise contamination can cause estimation bias and spatial leakage, problems that are exacerbated as the region of interest approaches the GRACE resolution limit of a few hundred km. Reliable estimates of water storage variations in small basins require compromises between competing needs for noise suppression and spatial resolution. The objective of this study was to quantitatively investigate processing methods and their impacts on bias, leakage, GRACE noise reduction, and estimated total error, allowing solution of the trade-offs. Among the methods tested is a recently developed concentration algorithm called spatiospectral localization, which optimizes the basin shape description, taking into account limited spatial resolution. This method is particularly suited to retrieval of basin-scale water storage variations and is effective for small basins. To increase confidence in derived methods, water storage variations were calculated for both CSR (Center for Space Research) and GRGS (Groupe de Recherche de Géodésie Spatiale) GRACE products, which employ different processing strategies. The processing techniques were tested on the intensively monitored High Plains Aquifer (450,000 km2 area), where application of the appropriate optimal processing method allowed retrieval of water storage variations over a portion of the aquifer as small as ˜200,000 km2.
Wang, J X; Hu, M G; Yu, S C; Xiao, G X
2017-09-10
Objective: To understand the spatial distribution of incidence of hand foot and mouth disease (HFMD) at scale of township and provide evidence for the better prevention and control of HFMD and allocation of medical resources. Methods: The incidence data of HFMD in 108 counties (district) in Shandong province in 2010 were collected. Downscaling interpolation was conducted by using area-to-area Poisson Kriging method. The interpolation results were visualized by using geographic information system (GIS). The county (district) incidence was interpolated into township incidence to get the distribution of spatial distribution of incidence of township. Results: In the downscaling interpolation, the range of the fitting semi-variance equation was 20.38 km. Within the range, the incidence had correlation with each other. The fitting function of scatter diagram of estimated and actual incidence of HFMD at country level was y =1.053 1 x , R (2)=0.99. The incidences at different scale were consistent. Conclusions: The incidence of HFMD had spatial autocorrelation within 20.38 km. When HFMD occurs in one place, it is necessary to strengthen the surveillance and allocation of medical resource in the surrounding area within 20.38 km. Area to area Poisson Kriging method based downscaling research can be used in spatial visualization of HFMD incidence.
Spatial Statistics of atmospheric particulate matter in China
NASA Astrophysics Data System (ADS)
Huang, Yongxiang; Wang, Yangjun; Liu, Yulu
2017-04-01
In this work, the spatial dynamics of the atmospheric particulate matters (resp. PM10 and PM2.5) are studied using turbulence methodologies. The hourly concentrations of particulate matter were released by the Chinese government (http://www.cnemc.cn). We first processed these data into daily average concentrations. Totally, there are 305 monitor stations with an observations period of 425 days. It is found experimentally that the spatial correlation function ρ(r) shows a log-law on the mesoscale range, i.e., 50 ≤ r ≤ 500 km, with an experimental scaling exponent β = 0.45. The spatial structure function shows a power-law behavior on the mesoscale range 90 ≤ r ≤ 500 km. The experimental scaling exponent ζ(q) is convex, showing that the intermittent correction is relevant in characterizing the spatial dynamics of particulate matter. The measured singularity spectrum f(α) also shows its multifractal nature. Experimentally, the particulate matter is more intermittent than the passive scalar, which could be partially due to the mesoscale movements of the atmosphere, and also due to local sources, such as local industry activities.
Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui
2009-01-01
The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.
NASA Astrophysics Data System (ADS)
Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady
2016-04-01
Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)
L-band Soil Moisture Mapping using Small UnManned Aerial Systems
NASA Astrophysics Data System (ADS)
Dai, E.
2015-12-01
Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions as low as 5 km for some products. However, there exists a need for measurements of soil moisture on smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform) .Compared with various other proposed methods of validation based on either situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed (~km scale) coverage at very high spatial resolution (~15 m) suitable for scaling scale studies, and at comparatively low operator cost. The LDCR on Tempest unit can supply the soil moisture mapping with different resolution which is of order the Tempest altitude.
Dispersal Patterns of Coastal Fish: Implications for Designing Networks of Marine Protected Areas
Di Franco, Antonio; Gillanders, Bronwyn M.; De Benedetto, Giuseppe; Pennetta, Antonio; De Leo, Giulio A.; Guidetti, Paolo
2012-01-01
Information about dispersal scales of fish at various life history stages is critical for successful design of networks of marine protected areas, but is lacking for most species and regions. Otolith chemistry provides an opportunity to investigate dispersal patterns at a number of life history stages. Our aim was to assess patterns of larval and post-settlement (i.e. between settlement and recruitment) dispersal at two different spatial scales in a Mediterranean coastal fish (i.e. white sea bream, Diplodus sargus sargus) using otolith chemistry. At a large spatial scale (∼200 km) we investigated natal origin of fish and at a smaller scale (∼30 km) we assessed “site fidelity” (i.e. post-settlement dispersal until recruitment). Larvae dispersed from three spawning areas, and a single spawning area supplied post-settlers (proxy of larval supply) to sites spread from 100 to 200 km of coastline. Post-settlement dispersal occurred within the scale examined of ∼30 km, although about a third of post-settlers were recruits in the same sites where they settled. Connectivity was recorded both from a MPA to unprotected areas and vice versa. The approach adopted in the present study provides some of the first quantitative evidence of dispersal at both larval and post-settlement stages of a key species in Mediterranean rocky reefs. Similar data taken from a number of species are needed to effectively design both single marine protected areas and networks of marine protected areas. PMID:22355388
Scale-dependent correlation of seabirds with schooling fish in a coastal ecosystem
Schneider, Davod C.; Piatt, John F.
1986-01-01
The distribution of piscivorous seabirds relative to schooling fish was investigated by repeated censusing of 2 intersecting transects in the Avalon Channel, which carries the Labrador Current southward along the east coast of Newfoundland. Murres (primarily common murres Uria aalge), Atlantic puffins Fratercula arctica, and schooling fish (primarily capelin Mallotus villosus) were highly aggregated at spatial scales ranging from 0.25 to 15 km. Patchiness of murres, puffins and schooling fish was scale-dependent, as indicated by significantly higher variance-to-mean ratios at large measurement distances than at the minimum distance, 0.25 km. Patch scale of puffins ranged from 2.5 to 15 km, of murres from 3 to 8.75 km, and of schooling fish from 1.25 to 15 km. Patch scale of birds and schooling fish was similar m 6 out of 9 comparisons. Correlation between seabirds and schooling birds was significant at the minimum measurement distance in 6 out of 12 comparisons. Correlation was scale-dependent, as indicated by significantly higher coefficients at large measurement distances than at the minimum distance. Tracking scale, as indicated by the maximum significant correlation between birds and schooling fish, ranged from 2 to 6 km. Our analysis showed that extended aggregations of seabirds are associated with extended aggregations of schooling fish and that correlation of these marine carnivores with their prey is scale-dependent.
Leppäranta, Matti; Lewis, John E; Heini, Anniina; Arvola, Lauri
2018-06-04
Spatial variability, an essential characteristic of lake ecosystems, has often been neglected in field research and monitoring. In this study, we apply spatial statistical methods for the key physics and chemistry variables and chlorophyll a over eight sampling dates in two consecutive years in a large (area 103 km 2 ) eutrophic boreal lake in southern Finland. In the four summer sampling dates, the water body was vertically and horizontally heterogenic except with color and DOC, in the two winter ice-covered dates DO was vertically stratified, while in the two autumn dates, no significant spatial differences in any of the measured variables were found. Chlorophyll a concentration was one order of magnitude lower under the ice cover than in open water. The Moran statistic for spatial correlation was significant for chlorophyll a and NO 2 +NO 3 -N in all summer situations and for dissolved oxygen and pH in three cases. In summer, the mass centers of the chemicals were within 1.5 km from the geometric center of the lake, and the 2nd moment radius ranged in 3.7-4.1 km respective to 3.9 km for the homogeneous situation. The lateral length scales of the studied variables were 1.5-2.5 km, about 1 km longer in the surface layer. The detected spatial "noise" strongly suggests that besides vertical variation also the horizontal variation in eutrophic lakes, in particular, should be considered when the ecosystems are monitored.
Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre
2015-01-01
Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate "wall-to-wall" remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution.
Daly, Ryan; Smale, Malcolm J.; Cowley, Paul D.; Froneman, Pierre W.
2014-01-01
Bull sharks (Carcharhinus leucas) are globally distributed top predators that play an important ecological role within coastal marine communities. However, little is known about the spatial and temporal scales of their habitat use and associated ecological role. In this study, we employed passive acoustic telemetry to investigate the residency patterns and migration dynamics of 18 adult bull sharks (195–283 cm total length) tagged in southern Mozambique for a period of between 10 and 22 months. The majority of sharks (n = 16) exhibited temporally and spatially variable residency patterns interspersed with migration events. Ten individuals undertook coastal migrations that ranged between 433 and 709 km (mean = 533 km) with eight of these sharks returning to the study site. During migration, individuals exhibited rates of movement between 2 and 59 km.d−1 (mean = 17.58 km.d−1) and were recorded travelling annual distances of between 450 and 3760 km (mean = 1163 km). Migration towards lower latitudes primarily took place in austral spring and winter and there was a significant negative correlation between residency and mean monthly sea temperature at the study site. This suggested that seasonal change is the primary driver behind migration events but further investigation is required to assess how foraging and reproductive activity may influence residency patterns and migration. Results from this study highlight the need for further understanding of bull shark migration dynamics and suggest that effective conservation strategies for this vulnerable species necessitate the incorporation of congruent trans-boundary policies over large spatial scales. PMID:25295972
L Benda; T.J. Beechie; R.C. Wissmar; A. Johnson
1992-01-01
Morphology and distribution of salmonid habitats were related to the geomorphology of a river basin at three spatial scales including reach (l02-103 m2), subbasin (2-26 km2), and the watershed (240 km2). Stream reaches on a young fluvial terrace (1700 yr...
Circumpolar variation in periodicity and synchrony among gypsy moth populations
Derek M. Johnson; Andrew M. Liebhold; Ottar N. Bjornstad; Michael L. Mcmanus; Michael L. Mcmanus
2005-01-01
Previous studies or insect dynamics have detected spatial synchrony in intraspecific population dynamics up to, but not exceeding, 1000 km. Oddly, interspecific synchrony has recently been reported at distances well over 1000 km (at continental and circumpolar scales). While the authors implicated climatic effects as the cause for the apparent largescale interspecific...
NASA Astrophysics Data System (ADS)
Tereshchenko, E. D.; Turyansky, V. A.; Khudukon, B. Z.; Yurik, R. Yu.; Frolov, V. L.
2018-01-01
We present the results of studying the characteristics of the artificial plasma structures excited in the ionospheric F2 region modified by high-power HF radio waves. The experiments were carried out at the Sura heating facility using satellite radio sounding of the ionosphere. The plasma density profile was reconstructed with the highest possible spatial resolution for today, about 4 km. In a direction close to the magnetic zenith of the pump wave, the following phenomena were observed: the formation of a cavity with a 15% lower plasma density at the altitudes of the F2 layer and below; the formation of an area with plasma density increased by 12% at altitudes greater than 400 km. With a long-term quasiperiodic impact of the pump wave on the ionosphere, wavy large-scale electron-density perturbations (the meridional scale λx ≈ 130 km and the vertical scale λz ≈ 440 km) are also formed above the Sura facility. These perturbations can be due to the plasma density modulation by an artificial acoustic-gravity wave with a period of 10.6 m, which was formed by the heat source inside a large-scale cavity with low plasma density; there is generation of the electron density irregularities for the electrons with ΔNe/Ne ≈ 3% in the form of layers having the sizes 10-12 km along and about 24 km across the geomagnetic field, which are found both below and above the F2-layer maximum. The mechanisms of the formation of these plasma structures are discussed.
NASA Astrophysics Data System (ADS)
Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.
2013-12-01
Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.
Volis, Sergei; Ormanbekova, Danara; Yermekbayev, Kanat; Song, Minshu; Shulgina, Irina
2015-01-01
Detecting local adaptation and its spatial scale is one of the most important questions of evolutionary biology. However, recognition of the effect of local selection can be challenging when there is considerable environmental variation across the distance at the whole species range. We analyzed patterns of local adaptation in emmer wheat, Triticum dicoccoides, at two spatial scales, small (inter-population distance less than one km) and large (inter-population distance more than 50 km) using several approaches. Plants originating from four distinct habitats at two geographic scales (cold edge, arid edge and two topographically dissimilar core locations) were reciprocally transplanted and their success over time was measured as 1) lifetime fitness in a year of planting, and 2) population growth four years after planting. In addition, we analyzed molecular (SSR) and quantitative trait variation and calculated the QST/FST ratio. No home advantage was detected at the small spatial scale. At the large spatial scale, home advantage was detected for the core population and the cold edge population in the year of introduction via measuring life-time plant performance. However, superior performance of the arid edge population in its own environment was evident only after several generations via measuring experimental population growth rate through genotyping with SSRs allowing counting the number of plants and seeds per introduced genotype per site. These results highlight the importance of multi-generation surveys of population growth rate in local adaptation testing. Despite predominant self-fertilization of T. dicoccoides and the associated high degree of structuring of genetic variation, the results of the QST - FST comparison were in general agreement with the pattern of local adaptation at the two spatial scales detected by reciprocal transplanting.
Norris, Darren; Fortin, Marie-Josée; Magnusson, William E.
2014-01-01
Background Ecological monitoring and sampling optima are context and location specific. Novel applications (e.g. biodiversity monitoring for environmental service payments) call for renewed efforts to establish reliable and robust monitoring in biodiversity rich areas. As there is little information on the distribution of biodiversity across the Amazon basin, we used altitude as a proxy for biological variables to test whether meso-scale variation can be adequately represented by different sample sizes in a standardized, regular-coverage sampling arrangement. Methodology/Principal Findings We used Shuttle-Radar-Topography-Mission digital elevation values to evaluate if the regular sampling arrangement in standard RAPELD (rapid assessments (“RAP”) over the long-term (LTER [“PELD” in Portuguese])) grids captured patters in meso-scale spatial variation. The adequacy of different sample sizes (n = 4 to 120) were examined within 32,325 km2/3,232,500 ha (1293×25 km2 sample areas) distributed across the legal Brazilian Amazon. Kolmogorov-Smirnov-tests, correlation and root-mean-square-error were used to measure sample representativeness, similarity and accuracy respectively. Trends and thresholds of these responses in relation to sample size and standard-deviation were modeled using Generalized-Additive-Models and conditional-inference-trees respectively. We found that a regular arrangement of 30 samples captured the distribution of altitude values within these areas. Sample size was more important than sample standard deviation for representativeness and similarity. In contrast, accuracy was more strongly influenced by sample standard deviation. Additionally, analysis of spatially interpolated data showed that spatial patterns in altitude were also recovered within areas using a regular arrangement of 30 samples. Conclusions/Significance Our findings show that the logistically feasible sample used in the RAPELD system successfully recovers meso-scale altitudinal patterns. This suggests that the sample size and regular arrangement may also be generally appropriate for quantifying spatial patterns in biodiversity at similar scales across at least 90% (≈5 million km2) of the Brazilian Amazon. PMID:25170894
NASA Astrophysics Data System (ADS)
Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.
2017-12-01
A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.
NASA Astrophysics Data System (ADS)
Leahy, Susannah M.; Russ, Garry R.; Abesamis, Rene A.
2015-12-01
Recent research has demonstrated that, despite a pelagic larval stage, many coral reef fishes disperse over relatively small distances, leading to well-connected populations on scales of 0-30 km. Although variation in key biological characteristics has been explored on the scale of 100-1000 s of km, it has rarely been explored at the scale relevant to actual larval dispersal and population connectivity on ecological timescales. In this study, we surveyed the habitat and collected specimens ( n = 447) of juvenile butterflyfish, Chaetodon vagabundus, at nine sites along an 80-km stretch of coastline in the central Philippines to identify variation in key life history parameters at a spatial scale relevant to population connectivity. Mean pelagic larval duration (PLD) was 24.03 d (SE = 0.16 d), and settlement size was estimated to be 20.54 mm total length (TL; SE = 0.61 mm). Both traits were spatially consistent, although this PLD is considerably shorter than that reported elsewhere. In contrast, post-settlement daily growth rates, calculated from otolith increment widths from 1 to 50 d post-settlement, varied strongly across the study region. Elevated growth rates were associated with rocky habitats that this species is known to recruit to, but were strongly negatively correlated with macroalgal cover and exhibited negative density dependence with conspecific juveniles. Larger animals had lower early (first 50 d post-settlement) growth rates than smaller animals, even after accounting for seasonal variation in growth rates. Both VBGF and Gompertz models provided good fits to post-settlement size-at-age data ( n = 447 fish), but the VBGF's estimate of asymptotic length ( L ∞ = 168 mm) was more consistent with field observations of maximum fish length. Our findings indicate that larval characteristics are consistent at the spatial scale at which populations are likely well connected, but that site-level biological differences develop post-settlement, most likely as a result of key differences in quality of recruitment habitat.
Liang, Jia Xin; Li, Xin Ju
2018-02-01
With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.
Chorus Whistler Wave Source Scales As Determined From Multipoint Van Allen Probe Measurements
NASA Technical Reports Server (NTRS)
Agapitov, O.; Blum, L. W.; Mozer, F. S.; Bonnell, J. W.; Wygant, J.
2017-01-01
Whistler mode chorus waves are particularly important in outer radiation belt dynamics due to their key role in controlling the acceleration and scattering of electrons over a very wide energy range. The key parameters for both nonlinear and quasi-linear treatment of wave-particle interactions are the temporal and spatial scales of the wave source region and coherence of the wave field perturbations. Neither the source scale nor the coherence scale is well established experimentally, mostly because of a lack of multipoint VLF waveform measurements. We present an unprecedentedly long interval of coordinated VLF waveform measurements (sampled at 16384 s(exp -1)) aboard the two Van Allen Probes spacecraft-9 h (0800-1200 UT and 1700-2200 UT) during two consecutive apogees on 15 July 2014. The spacecraft separations varied from about 100 to 5000 km (mostly radially); measurements covered an L shell range from 3 to 6; magnetic local time 0430-0900, and magnetic latitudes were approximately 15 and approximately 5 deg during the two orbits. Using time-domain correlation techniques, the single chorus source spatial extent transverse to the background magnetic field has been determined to be about 550-650 km for upper band chorus waves with amplitudes less than 100 pT and up to 800 km for larger amplitude, lower band chorus waves. The ratio between wave amplitudes measured on the two spacecraft is also examined to reveal that the wave amplitude distribution within a single chorus element generation area can be well approximated by a Gaussian exp(-0.5 x r (exp 2)/r(sub 0)(exp 2)), with the characteristic scale r(sub 0) around 300 km. Waves detected by the two spacecraft were found to be coherent in phase at distances up to 400 km.
Karanth, Kota Ullas; Gopalaswamy, Arjun M.; Kumar, Narayanarao Samba; Vaidyanathan, Srinivas; Nichols, James D.; MacKenzie, Darryl I.
2011-01-01
1. Assessing spatial distributions of threatened large carnivores at landscape scales poses formidable challenges because of their rarity and elusiveness. As a consequence of logistical constraints, investigators typically rely on sign surveys. Most survey methods, however, do not explicitly address the central problem of imperfect detections of animal signs in the field, leading to underestimates of true habitat occupancy and distribution. 2. We assessed habitat occupancy for a tiger Panthera tigris metapopulation across a c. 38 000-km2 landscape in India, employing a spatially replicated survey to explicitly address imperfect detections. Ecological predictions about tiger presence were confronted with sign detection data generated from occupancy sampling of 205 sites, each of 188 km2. 3. A recent occupancy model that considers Markovian dependency among sign detections on spatial replicates performed better than the standard occupancy model (ΔAIC = 184·9). A formulation of this model that fitted the data best showed that density of ungulate prey and levels of human disturbance were key determinants of local tiger presence. Model averaging resulted in a replicate-level detection probability [inline image] = 0·17 (0·17) for signs and a tiger habitat occupancy estimate of [inline image] = 0·665 (0·0857) or 14 076 (1814) km2 of potential habitat of 21 167 km2. In contrast, a traditional presence-versus-absence approach underestimated occupancy by 47%. Maps of probabilities of local site occupancy clearly identified tiger source populations at higher densities and matched observed tiger density variations, suggesting their potential utility for population assessments at landscape scales. 4. Synthesis and applications. Landscape-scale sign surveys can efficiently assess large carnivore spatial distributions and elucidate the factors governing their local presence, provided ecological and observation processes are both explicitly modelled. Occupancy sampling using spatial replicates can be used to reliably and efficiently identify tiger population sources and help monitor metapopulations. Our results reinforce earlier findings that prey depletion and human disturbance are key drivers of local tiger extinctions and tigers can persist even in human-dominated landscapes through effective protection of source populations. Our approach facilitates efficient targeting of tiger conservation interventions and, more generally, provides a basis for the reliable integration of large carnivore monitoring data between local and landscape scales.
Hernández, Jaime; Núñez, Ignacia; Bacigalupo, Antonella; Cattan, Pedro E
2013-05-31
Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area. Vector's locations were obtained with a rural householders' survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids. The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range. The methodology presented here was useful to model the distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study's methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases.
2013-01-01
Background Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area. Methods Vector’s locations were obtained with a rural householders’ survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids. Results The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range. Conclusions The methodology presented here was useful to model the distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study’s methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases. PMID:23724993
Scaling properties of the Arctic sea ice Deformation from Buoy Dispersion Analysis
NASA Astrophysics Data System (ADS)
Weiss, J.; Rampal, P.; Marsan, D.; Lindsay, R.; Stern, H.
2007-12-01
A temporal and spatial scaling analysis of Arctic sea ice deformation is performed over time scales from 3 hours to 3 months and over spatial scales from 300 m to 300 km. The deformation is derived from the dispersion of pairs of drifting buoys, using the IABP (International Arctic Buoy Program) buoy data sets. This study characterizes the deformation of a very large solid plate -the Arctic sea ice cover- stressed by heterogeneous forcing terms like winds and ocean currents. It shows that the sea ice deformation rate depends on the scales of observation following specific space and time scaling laws. These scaling properties share similarities with those observed for turbulent fluids, especially for the ocean and the atmosphere. However, in our case, the time scaling exponent depends on the spatial scale, and the spatial exponent on the temporal scale, which implies a time/space coupling. An analysis of the exponent values shows that Arctic sea ice deformation is very heterogeneous and intermittent whatever the scales, i.e. it cannot be considered as viscous-like, even at very large time and/or spatial scales. Instead, it suggests a deformation accommodated by a multi-scale fracturing/faulting processes.
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.
Evaluation of the high resolution DEHM/UBM model system over Denmark
NASA Astrophysics Data System (ADS)
Im, Ulas; Christensen, Jesper H.; Ellermann, Thomas; Ketzel, Matthias; Geels, Camilla; Hansen, Kaj M.; Plejdrup, Marlene S.; Brandt, Jørgen
2015-04-01
The air pollutant levels over Denmark are simulated using the high resolution DEHM/UBM model system for the years 2006 to 2014. The system employs a hemispheric chemistry-transport model, the Danish Eulerian Hemispheric Model (DEHM; Brandt et al., 2012) that runs on a 150 km x 150 km resolution over the Northern Hemisphere, with nesting capability for higher resolutions over Europe, Northern Europe and Denmark on 50 km x 50 km, 16.7 km x 16.7 km and 5.6 km x 5.6 km resolutions, respectively, coupled to the Urban Background Model (UBM; Berkowicz, 2000; Brandt et al., 2001) that covers the whole of Denmark with a 1 km x 1 km spatial resolution. Over Denmark, the system uses the SPREAD emission model (Plejdrup and Gyldenkærne, 2011) that distributes the Danish emissions for all pollutants and all sectors in the national emission database on a 1 km x 1 km resolution grid covering Denmark and its national sea territory. The study will describe the model system and we will evaluate the performance of the model system in simulating hourly and daily ozone (O3), carbon monoxide (CO), nitrogen monoxide (NO), nitrogen dioxide (NO2) and particulate matter (PM10 and PM2.5) concentrations against surface measurements from eight monitoring stations. Finally we investigate the spatial variation of air pollutants over Denmark on different time scales. References Berkowicz, R., 2000. A Simple Model for Urban Background Pollution. Environmental Monitoring and Assessment, 65, 1/2, 259-267. Brandt, J., J. H. Christensen, L. M. Frohn, F. Palmgren, R. Berkowicz and Z. Zlatev, 2001: "Operational air pollution forecasts from European to local scale". Atmospheric Environment, Vol. 35, Sup. No. 1, pp. S91-S98, 2001 Brandt et al., 2012. An integrated model study for Europe and North America using the Danish Eulerian Hemispheric Model with focus on intercontinental transport. Atmospheric Environment, 53, 156-176. Plejdrup, M.S., Gyldenkærne, S., 2011. Spatial distribution of pollutants to air - the SPREAD model. NERI Technical Report No. 823.
NASA Astrophysics Data System (ADS)
Saito, S.; Yoshihara, T.
2017-08-01
Associated with plasma bubbles, extreme spatial gradients in ionospheric total electron content (TEC) were observed on 8 April 2008 at Ishigaki (24.3°N, 124.2°E, +19.6° magnetic latitude), Japan. The largest gradient was 3.38 TECU km-1 (total electron content unit, 1 TECU = 1016 el m-2), which is equivalent to an ionospheric delay gradient of 540 mm km-1 at the GPS L1 frequency (1.57542 GHz). This value is confirmed by using multiple estimating methods. The observed value exceeds the maximum ionospheric gradient that has ever been observed (412 mm km-1 or 2.59 TECU km-1) to be associated with a severe magnetic storm. It also exceeds the assumed maximum value (500 mm km-1 or 3.08 TECU km-1) which was used to validate the draft international standard for Global Navigation Satellite System (GNSS) Ground-Based Augmentation Systems (GBAS) to support Category II/III approaches and landings. The steepest part of this extreme gradient had a scale size of 5.3 km, and the front-normal velocities were estimated to be 71 m s-1 with a wavefront-normal direction of east-northeastward. The total width of the transition region from outside to inside the plasma bubble was estimated to be 35.3 km. The gradient of relatively small spatial scale size may fall between an aircraft and a GBAS ground subsystem and may be undetectable by both aircraft and ground.
Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.
NASA Astrophysics Data System (ADS)
Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric
2016-04-01
SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.
Multi-scale hydrometeorological observation and modelling for flash flood understanding
NASA Astrophysics Data System (ADS)
Braud, I.; Ayral, P.-A.; Bouvier, C.; Branger, F.; Delrieu, G.; Le Coz, J.; Nord, G.; Vandervaere, J.-P.; Anquetin, S.; Adamovic, M.; Andrieu, J.; Batiot, C.; Boudevillain, B.; Brunet, P.; Carreau, J.; Confoland, A.; Didon-Lescot, J.-F.; Domergue, J.-M.; Douvinet, J.; Dramais, G.; Freydier, R.; Gérard, S.; Huza, J.; Leblois, E.; Le Bourgeois, O.; Le Boursicaud, R.; Marchand, P.; Martin, P.; Nottale, L.; Patris, N.; Renard, B.; Seidel, J.-L.; Taupin, J.-D.; Vannier, O.; Vincendon, B.; Wijbrans, A.
2014-09-01
This paper presents a coupled observation and modelling strategy aiming at improving the understanding of processes triggering flash floods. This strategy is illustrated for the Mediterranean area using two French catchments (Gard and Ardèche) larger than 2000 km2. The approach is based on the monitoring of nested spatial scales: (1) the hillslope scale, where processes influencing the runoff generation and its concentration can be tackled; (2) the small to medium catchment scale (1-100 km2), where the impact of the network structure and of the spatial variability of rainfall, landscape and initial soil moisture can be quantified; (3) the larger scale (100-1000 km2), where the river routing and flooding processes become important. These observations are part of the HyMeX (HYdrological cycle in the Mediterranean EXperiment) enhanced observation period (EOP), which will last 4 years (2012-2015). In terms of hydrological modelling, the objective is to set up regional-scale models, while addressing small and generally ungauged catchments, which represent the scale of interest for flood risk assessment. Top-down and bottom-up approaches are combined and the models are used as "hypothesis testing" tools by coupling model development with data analyses in order to incrementally evaluate the validity of model hypotheses. The paper first presents the rationale behind the experimental set-up and the instrumentation itself. Second, we discuss the associated modelling strategy. Results illustrate the potential of the approach in advancing our understanding of flash flood processes on various scales.
Multi-scale hydrometeorological observation and modelling for flash-flood understanding
NASA Astrophysics Data System (ADS)
Braud, I.; Ayral, P.-A.; Bouvier, C.; Branger, F.; Delrieu, G.; Le Coz, J.; Nord, G.; Vandervaere, J.-P.; Anquetin, S.; Adamovic, M.; Andrieu, J.; Batiot, C.; Boudevillain, B.; Brunet, P.; Carreau, J.; Confoland, A.; Didon-Lescot, J.-F.; Domergue, J.-M.; Douvinet, J.; Dramais, G.; Freydier, R.; Gérard, S.; Huza, J.; Leblois, E.; Le Bourgeois, O.; Le Boursicaud, R.; Marchand, P.; Martin, P.; Nottale, L.; Patris, N.; Renard, B.; Seidel, J.-L.; Taupin, J.-D.; Vannier, O.; Vincendon, B.; Wijbrans, A.
2014-02-01
This paper presents a coupled observation and modelling strategy aiming at improving the understanding of processes triggering flash floods. This strategy is illustrated for the Mediterranean area using two French catchments (Gard and Ardèche) larger than 2000 km2. The approach is based on the monitoring of nested spatial scales: (1) the hillslope scale, where processes influencing the runoff generation and its concentration can be tackled; (2) the small to medium catchment scale (1-100 km2) where the impact of the network structure and of the spatial variability of rainfall, landscape and initial soil moisture can be quantified; (3) the larger scale (100-1000 km2) where the river routing and flooding processes become important. These observations are part of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) Enhanced Observation Period (EOP) and lasts four years (2012-2015). In terms of hydrological modelling the objective is to set up models at the regional scale, while addressing small and generally ungauged catchments, which is the scale of interest for flooding risk assessment. Top-down and bottom-up approaches are combined and the models are used as "hypothesis testing" tools by coupling model development with data analyses, in order to incrementally evaluate the validity of model hypotheses. The paper first presents the rationale behind the experimental set up and the instrumentation itself. Second, we discuss the associated modelling strategy. Results illustrate the potential of the approach in advancing our understanding of flash flood processes at various scales.
NASA Astrophysics Data System (ADS)
Matsui, H.; Koike, M.; Kondo, Y.; Takegawa, N.; Kita, K.; Miyazaki, Y.; Hu, M.; Chang, S.-Y.; Blake, D. R.; Fast, J. D.; Zaveri, R. A.; Streets, D. G.; Zhang, Q.; Zhu, T.
2009-01-01
Regional aerosol model calculations were made using the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) and WRF-chem models to study spatial and temporal variations of aerosols around Beijing, China, in the summer of 2006, when the Campaigns of Air Quality Research in Beijing and Surrounding Region 2006 (CAREBeijing) intensive campaign was conducted. Model calculations captured temporal variations of primary (such as elemental carbon (EC)) and secondary (such as sulfate) aerosols observed in and around Beijing. The spatial distributions of aerosol optical depth observed by the MODIS satellite sensors were also reproduced over northeast China. Model calculations showed distinct differences in spatial distributions between primary and secondary aerosols in association with synoptic-scale meteorology. Secondary aerosols increased in air around Beijing on a scale of about 1000 × 1000 km2 under an anticyclonic pressure system. This air mass was transported northward from the high anthropogenic emission area extending south of Beijing with continuous photochemical production. Subsequent cold front passage brought clean air from the north, and polluted air around Beijing was swept to the south of Beijing. This cycle was repeated about once a week and was found to be responsible for observed enhancements/reductions of aerosols at the intensive measurement sites. In contrast to secondary aerosols, the spatial distributions of primary aerosols (EC) reflected those of emissions, resulting in only slight variability despite the changes in synoptic-scale meteorology. In accordance with these results, source apportionment simulations revealed that primary aerosols around Beijing were controlled by emissions within 100 km around Beijing within the preceding 24 h, while emissions as far as 500 km and within the preceding 3 days were found to affect secondary aerosols.
Linking Time and Space Scales in Distributed Hydrological Modelling - a case study for the VIC model
NASA Astrophysics Data System (ADS)
Melsen, Lieke; Teuling, Adriaan; Torfs, Paul; Zappa, Massimiliano; Mizukami, Naoki; Clark, Martyn; Uijlenhoet, Remko
2015-04-01
One of the famous paradoxes of the Greek philosopher Zeno of Elea (~450 BC) is the one with the arrow: If one shoots an arrow, and cuts its motion into such small time steps that at every step the arrow is standing still, the arrow is motionless, because a concatenation of non-moving parts does not create motion. Nowadays, this reasoning can be refuted easily, because we know that motion is a change in space over time, which thus by definition depends on both time and space. If one disregards time by cutting it into infinite small steps, motion is also excluded. This example shows that time and space are linked and therefore hard to evaluate separately. As hydrologists we want to understand and predict the motion of water, which means we have to look both in space and in time. In hydrological models we can account for space by using spatially explicit models. With increasing computational power and increased data availability from e.g. satellites, it has become easier to apply models at a higher spatial resolution. Increasing the resolution of hydrological models is also labelled as one of the 'Grand Challenges' in hydrology by Wood et al. (2011) and Bierkens et al. (2014), who call for global modelling at hyperresolution (~1 km and smaller). A literature survey on 242 peer-viewed articles in which the Variable Infiltration Capacity (VIC) model was used, showed that the spatial resolution at which the model is applied has decreased over the past 17 years: From 0.5 to 2 degrees when the model was just developed, to 1/8 and even 1/32 degree nowadays. On the other hand the literature survey showed that the time step at which the model is calibrated and/or validated remained the same over the last 17 years; mainly daily or monthly. Klemeš (1983) stresses the fact that space and time scales are connected, and therefore downscaling the spatial scale would also imply downscaling of the temporal scale. Is it worth the effort of downscaling your model from 1 degree to 1/24 degree, if in the end you only look at monthly runoff? In this study an attempt is made to link time and space scales in the VIC model, to study the added value of a higher spatial resolution-model for different time steps. In order to do this, four different VIC models were constructed for the Thur basin in North-Eastern Switzerland (1700 km²), a tributary of the Rhine: one lumped model, and three spatially distributed models with a resolution of respectively 1x1 km, 5x5 km, and 10x10 km. All models are run at an hourly time step and aggregated and calibrated for different time steps (hourly, daily, monthly, yearly) using a novel Hierarchical Latin Hypercube Sampling Technique (Vořechovský, 2014). For each time and space scale, several diagnostics like Nash-Sutcliffe efficiency, Kling-Gupta efficiency, all the quantiles of the discharge etc., are calculated in order to compare model performance over different time and space scales for extreme events like floods and droughts. Next to that, the effect of time and space scale on the parameter distribution can be studied. In the end we hope to find a link for optimal time and space scale combinations.
NASA Astrophysics Data System (ADS)
Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan
2017-10-01
Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.
Larval fish dispersal in a coral-reef seascape.
Almany, Glenn R; Planes, Serge; Thorrold, Simon R; Berumen, Michael L; Bode, Michael; Saenz-Agudelo, Pablo; Bonin, Mary C; Frisch, Ashley J; Harrison, Hugo B; Messmer, Vanessa; Nanninga, Gerrit B; Priest, Mark A; Srinivasan, Maya; Sinclair-Taylor, Tane; Williamson, David H; Jones, Geoffrey P
2017-05-08
Larval dispersal is a critical yet enigmatic process in the persistence and productivity of marine metapopulations. Empirical data on larval dispersal remain scarce, hindering the use of spatial management tools in efforts to sustain ocean biodiversity and fisheries. Here we document dispersal among subpopulations of clownfish (Amphiprion percula) and butterflyfish (Chaetodon vagabundus) from eight sites across a large seascape (10,000 km 2 ) in Papua New Guinea across 2 years. Dispersal of clownfish was consistent between years, with mean observed dispersal distances of 15 km and 10 km in 2009 and 2011, respectively. A Laplacian statistical distribution (the dispersal kernel) predicted a mean dispersal distance of 13-19 km, with 90% of settlement occurring within 31-43 km. Mean dispersal distances were considerably greater (43-64 km) for butterflyfish, with kernels declining only gradually from spawning locations. We demonstrate that dispersal can be measured on spatial scales sufficient to inform the design of and test the performance of marine reserve networks.
COMMUNITY-SCALE MODELING FOR AIR TOXICS AND HOMELAND SECURITY
The purpose of this task is to develop and evaluate numerical and physical modeling tools for simulating ambient concentrations of airborne substances in urban settings at spatial scales ranging from <1-10 km. Research under this task will support client needs in human exposure ...
Diakaridia, Sanogo; Pan, Yue; Xu, Pengbai; Zhou, Dengwang; Wang, Benzhang; Teng, Lei; Lu, Zhiwei; Ba, Dexin; Dong, Yongkang
2017-07-24
In distributed Brillouin optical fiber sensor when the length of the perturbation to be detected is much smaller than the spatial resolution that is defined by the pulse width, the measured Brillouin gain spectrum (BGS) experiences two or multiple peaks. In this work, we propose and demonstrate a technique using differential pulse pair Brillouin optical time-domain analysis (DPP-BOTDA) based on double-peak BGS to enhance small-scale events detection capability, where two types of single mode fiber (main fiber and secondary fiber) with 116 MHz Brillouin frequency shift (BFS) difference have been used. We have realized detection of a 5-cm hot spot at the far end of 24-km single mode fiber by employing a 50-cm spatial resolution DPP-BOTDA with only 1GS/s sampling rate (corresponding to 10 cm/point). The BFS at the far end of 24-km sensing fiber has been measured with 0.54 MHz standard deviation which corresponds to a 0.5°C temperature accuracy. This technique is simple and cost effective because it is implemented using the similar experimental setup of the standard BOTDA, however, it should be noted that the consecutive small-scale events have to be separated by a minimum length corresponding to the spatial resolution defined by the pulse width difference.
NASA Astrophysics Data System (ADS)
Gentry, D.; Amador, E. S.; Cable, M. L.; Cantrell, T.; Chaudry, N.; Cullen, T.; Duca, Z. A.; Jacobsen, M. B.; McCaig, H. C.; Murukesan, G.; Rennie, V.; Schwieterman, E. W.; Stevens, A. H.; Tan, G.; Yin, C.; Stockton, A.; Cullen, D.; Geppert, W.
2015-12-01
Exploration missions to Mars rely on rovers to perform deep analyses over small sampling areas; however, landing site selection is done using large-scale but low-resolution remote sensing data. Using Earth analogue environments to estimate the small-scale spatial and temporal distributions of key geochemical signatures and (for habitability studies) biomarkers helps ensure that the chosen sampling strategies meet mission science goals. We conducted two rounds of analogue expeditions to recent Icelandic lava fields. In July 2013, we tested correlation between three common biomarker assays: cell quantification via fluorescence microscopy, ATP quantification via bioluminescence, and quantitative PCR with universal primer sets. Sample sites were nested at four spatial scales (1 m, 10 m, 100 m, and > 1 km) and homogeneous at 'remote imaging' resolution (overall temperature, apparent moisture content, and regolith grain size). All spatial scales were highly diverse in ATP, bacterial 16S, and archaeal 16S DNA content; nearly half of sites were statistically different in ATP content at α = 0.05. Cell counts showed significant variation at the 10 m and 100 m scale; at the > 1 km scale, the mean counts were not distinguishable, but the median counts were, indicating differences in underlying distribution. Fungal 18S DNA content similarly varied at 1 m, 10 m, and 100 m scales only. Cell counts were not correlated with ATP or DNA content at any scale. ATP concentration and DNA content for all three primer sets were positively correlated. Bacterial DNA content was positively correlated with archaeal and fungal DNA content, though archaeal correlation was weak. Fungal and archaeal correlation was borderline. In July 2015, we repeated the sampling strategy, with the addition of a smaller-scale sampling grid of 10 cm and a third > 1 km location. This expedition also measured reflectance of the tephra cover and preserved mineral samples for future Raman spectroscopy in order to better distinguish between effects of geochemical variation and intrinsic biomarker variation.
Soil nutrients influence spatial distributions of tropical tree species
John, Robert; Dalling, James W.; Harms, Kyle E.; Yavitt, Joseph B.; Stallard, Robert F.; Mirabello, Matthew; Hubbell, Stephen P.; Valencia, Renato; Navarrete, Hugo; Vallejo, Martha; Foster, Robin B.
2007-01-01
The importance of niche vs. neutral assembly mechanisms in structuring tropical tree communities remains an important unsettled question in community ecology [Bell G (2005) Ecology 86:1757–1770]. There is ample evidence that species distributions are determined by soils and habitat factors at landscape (<104 km2) and regional scales. At local scales (<1 km2), however, habitat factors and species distributions show comparable spatial aggregation, making it difficult to disentangle the importance of niche and dispersal processes. In this article, we test soil resource-based niche assembly at a local scale, using species and soil nutrient distributions obtained at high spatial resolution in three diverse neotropical forest plots in Colombia (La Planada), Ecuador (Yasuni), and Panama (Barro Colorado Island). Using spatial distribution maps of >0.5 million individual trees of 1,400 species and 10 essential plant nutrients, we used Monte Carlo simulations of species distributions to test plant–soil associations against null expectations based on dispersal assembly. We found that the spatial distributions of 36–51% of tree species at these sites show strong associations to soil nutrient distributions. Neutral dispersal assembly cannot account for these plant–soil associations or the observed niche breadths of these species. These results indicate that belowground resource availability plays an important role in the assembly of tropical tree communities at local scales and provide the basis for future investigations on the mechanisms of resource competition among tropical tree species. PMID:17215353
Scaling properties of sea ice deformation from buoy dispersion analysis
NASA Astrophysics Data System (ADS)
Rampal, P.; Weiss, J.; Marsan, D.; Lindsay, R.; Stern, H.
2008-03-01
A temporal and spatial scaling analysis of Arctic sea ice deformation is performed over timescales from 3 h to 3 months and over spatial scales from 300 m to 300 km. The deformation is derived from the dispersion of pairs of drifting buoys, using the IABP (International Arctic Buoy Program) buoy data sets. This study characterizes the deformation of a very large solid plate (the Arctic sea ice cover) stressed by heterogeneous forcing terms like winds and ocean currents. It shows that the sea ice deformation rate depends on the scales of observation following specific space and time scaling laws. These scaling properties share similarities with those observed for turbulent fluids, especially for the ocean and the atmosphere. However, in our case, the time scaling exponent depends on the spatial scale, and the spatial exponent on the temporal scale, which implies a time/space coupling. An analysis of the exponent values shows that Arctic sea ice deformation is very heterogeneous and intermittent whatever the scales, i.e., it cannot be considered as viscous-like, even at very large time and/or spatial scales. Instead, it suggests a deformation accommodated by a multiscale fracturing/faulting processes.
Using GPS TEC measurements to probe ionospheric spatial spectra at mid-latitudes
NASA Astrophysics Data System (ADS)
Lay, E. H.; Parker, P. A.; Light, M. E.; Carrano, C. S.; Debchoudhury, S.; Haaser, R. A.
2017-12-01
The physics of how random ionospheric structure causes signal degradation is well understood as weak forward scattering through an effective diffraction grating created by plasma irregularities in the ionosphere. However, the spatial scale spectrum of those irregularities required for input into scintillation models and models of traveling ionospheric disturbances is poorly characterized, particularly at the kilometer to tens of kilometer scale lengths important for very-high-frequency (VHF) scintillation prediction. Furthermore, the majority of characterization studies have been performed in low-latitude or high-latitude regions where geomagnetic activity dominates the physical processes. At mid-latitudes, tropospheric and geomagnetic phenomena compete in disturbing the ionosphere, and it is not well understood how these multiple sources affect the drivers that influence the spatial spectrum. In this study, we are interested in mid-latitude electron density irregularities on the order of 10s of kilometers that would affect VHF signals. Data from the GPS networks Japan GEONET and the Plate Boundary Observatory (PBO, UNAVCO) in the western United States were analyzed for this study. Japan GEONET is a dense network of GPS receivers (station spacing of tens of km), with fairly evenly spaced positions over all of Japan. The PBO, on the other hand, has several pockets of extremely dense coverage (station spacing within a few km), but is less dense on average. We analyze a day with a large solar storm (2015/03/17, St. Patrick's Day Storm) to allow high scintillation potential at mid-latitudes, a day with low geomagnetic activity and low thunderstorm activity (2016/01/31), and a day with low geomagnetic activity and high thunderstorm activity (2015/08/02). We then perform two-dimensional spatial analyses on the TEC data from these two networks on scale lengths of 20 to 200 km to infer the spatial scale spectra.
Le Pichon, Céline; Tales, Évelyne; Belliard, Jérôme; Torgersen, Christian E.
2017-01-01
Spatially intensive sampling by electrofishing is proposed as a method for quantifying spatial variation in fish assemblages at multiple scales along extensive stream sections in headwater catchments. We used this method to sample fish species at 10-m2 points spaced every 20 m throughout 5 km of a headwater stream in France. The spatially intensive sampling design provided information at a spatial resolution and extent that enabled exploration of spatial heterogeneity in fish assemblage structure and aquatic habitat at multiple scales with empirical variograms and wavelet analysis. These analyses were effective for detecting scales of periodicity, trends, and discontinuities in the distribution of species in relation to tributary junctions and obstacles to fish movement. This approach to sampling riverine fishes may be useful in fisheries research and management for evaluating stream fish responses to natural and altered habitats and for identifying sites for potential restoration.
SoilGrids1km — Global Soil Information Based on Automated Mapping
Hengl, Tomislav; de Jesus, Jorge Mendes; MacMillan, Robert A.; Batjes, Niels H.; Heuvelink, Gerard B. M.; Ribeiro, Eloi; Samuel-Rosa, Alessandro; Kempen, Bas; Leenaars, Johan G. B.; Walsh, Markus G.; Gonzalez, Maria Ruiperez
2014-01-01
Background Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg−1), soil pH, sand, silt and clay fractions (%), bulk density (kg m−3), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha−1), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at a resolution and consistency not previously available. Some of the main limitations of the current version of SoilGrids1km are: (1) weak relationships between soil properties/classes and explanatory variables due to scale mismatches, (2) difficulty to obtain covariates that capture soil forming factors, (3) low sampling density and spatial clustering of soil profile locations. However, as the SoilGrids system is highly automated and flexible, increasingly accurate predictions can be generated as new input data become available. SoilGrids1km are available for download via http://soilgrids.org under a Creative Commons Non Commercial license. PMID:25171179
NASA Astrophysics Data System (ADS)
Steyaert, L. T.; Hall, F. G.; Loveland, T. R.
1997-12-01
A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km × 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within the wet conifer mosaic. Major differences in the 1-km AVHRR and 30-m Landsat TM-derived land cover classes are most likely due to differences in the spatial resolution of the data sets. In general, the 1 km AVHRR land cover classes are vegetation mosaics consisting of mixed combinations of the Landsat classes. Detailed mapping of the global boreal forest with this approach will benefit from algorithms for cloud screening and to atmospherically correct reflectance data for both aerosol and water vapor effects. We believe that this 1 km AVHRR land cover analysis provides new and useful information for regional water, energy, carbon, and trace gases studies in BOREAS, especially given the significant spatial variability in land cover type and associated biophysical land cover parameters (e.g., albedo, leaf area index, FPAR, and surface roughness). Multiresolution land cover comparisons (30 m, l km, and 100 km grid cells) also illustrated how heterogeneous landscape patterns are represented in land cover maps with differing spatial scales and provided insights on the requirements and challenges for parameterizing landscape heterogeneity as part of land surface process research.
Steyaert, L.T.; Hall, F.G.; Loveland, Thomas R.
1997-01-01
A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within the wet conifer mosaic. Major differences in the 1-km AVHRR and 30-m Landsat TM-derived land cover classes are most likely due to differences in the spatial resolution of the data sets. In general, the 1 km AVHRR land cover classes are vegetation mosaics consisting of mixed combinations of the Landsat classes. Detailed mapping of the global boreal forest with this approach will benefit from algorithms for cloud screening and to atmospherically correct reflectance data for both aerosol and water vapor effects. We believe that this 1 km AVHRR land cover analysis provides new and useful information for regional water, energy, carbon, and trace gases studies in BOREAS, especially given the significant spatial variability in land cover type and associated biophysical land cover parameters (e.g., albedo, leaf area index, FPAR, and surface roughness). Multiresolution land cover comparisons (30 m, 1 km, and 100 km grid cells) also illustrated how heterogeneous landscape patterns are represented in land cover maps with differing spatial scales and provided insights on the requirements and challenges for parameterizing landscape heterogeneity as part of land surface process research.
NASA Astrophysics Data System (ADS)
Burke, Sophia; Mulligan, Mark
2017-04-01
WaterWorld is a widely used spatial hydrological policy support system. The last user census indicates regular use by 1029 institutions across 141 countries. A key feature of WaterWorld since 2001 is that it comes pre-loaded with all of the required data for simulation anywhere in the world at a 1km or 1 ha resolution. This means that it can be easily used, without specialist technical ability, to examine baseline hydrology and the impacts of scenarios for change or management interventions to support policy formulation, hence its labelling as a policy support system. WaterWorld is parameterised by an extensive global gridded database of more than 600 variables, developed from many sources, since 1998, the so-called simTerra database. All of these data are available globally at 1km resolution and some variables (terrain, land cover, urban areas, water bodies) are available globally at 1ha resolution. If users have access to better data than is pre-loaded, they can upload their own data. WaterWorld is generally applied at the national or basin scale at 1km resolution, or locally (for areas of <10,000km2) at 1ha resolution, though continental (1km resolution) and global (10km resolution) applications are possible so it is a model with local to global applications. WaterWorld requires some 140 maps to run including monthly climate data, land cover and use, terrain, population, water bodies and more. Whilst publically-available terrain and land cover data are now well developed for local scale application, climate and land use data remain a challenge, with most global products being available at 1km or 10km resolution or worse, which is rather coarse for local application. As part of the EartH2Observe project we have used WFDEI (WATCH Forcing Data methodology applied to ERA-Interim data) at 1km resolution to provide an alternative input to WaterWorld's preloaded climate data. Here we examine the impacts of that on key hydrological outputs: water balance, water quality and outline the remaining challenges of using datasets like these for local scale application.
DETECTION OF SMALL-SCALE GRANULAR STRUCTURES IN THE QUIET SUN WITH THE NEW SOLAR TELESCOPE
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abramenko, V. I.; Yurchyshyn, V. B.; Goode, P. R.
2012-09-10
Results of a statistical analysis of solar granulation are presented. A data set of 36 images of a quiet-Sun area on the solar disk center was used. The data were obtained with the 1.6 m clear aperture New Solar Telescope at Big Bear Solar Observatory and with a broadband filter centered at the TiO (705.7 nm) spectral line. The very high spatial resolution of the data (diffraction limit of 77 km and pixel scale of 0.''0375) augmented by the very high image contrast (15.5% {+-} 0.6%) allowed us to detect for the first time a distinct subpopulation of mini-granular structures.more » These structures are dominant on spatial scales below 600 km. Their size is distributed as a power law with an index of -1.8 (which is close to the Kolmogorov's -5/3 law) and no predominant scale. The regular granules display a Gaussian (normal) size distribution with a mean diameter of 1050 km. Mini-granular structures contribute significantly to the total granular area. They are predominantly confined to the wide dark lanes between regular granules and often form chains and clusters, but different from magnetic bright points. A multi-fractality test reveals that the structures smaller than 600 km represent a multi-fractal, whereas on larger scales the granulation pattern shows no multi-fractality and can be considered as a Gaussian random field. The origin, properties, and role of the population of mini-granular structures in the solar magnetoconvection are yet to be explored.« less
SCOPE : Future Formation-Flying Magnetospheric Satellite Mission
NASA Astrophysics Data System (ADS)
Saito, Yoshifumi
A formation flight satellite mission "SCOPE" is now under study aiming at launching in 2017. "SCOPE" stands for ‘cross Scale COupling in the Plasma universE'. The main purpose of this mission is to investigate the dynamic behaviors of plasma in the terrestrial magnetosphere that range over magnitudes of both temporal and spatial scales. The basic idea of the SCOPE mission is to distinguish temporal and spatial variations of physical processes by putting five formation flight spacecraft into the key regions of the Earth's magnetosphere. The formation consists of one large mother satellite and four small daughter satellites. Three of the four daughter satellites surround the mother satellite 3-dimensionally maintaining the mutual distances of variable ranges between 5 km and 5000 km. The fourth daughter satellite stays near the mother satellite with the distance between 5 km and 100 km. By this configuration, we can obtain both the macro-scale (1000 km - 5000 km) and micro-scale (¡ 100 km) information about the plasma disturbances at the same time. The launcher for SCOPE has been assumed to be M-V rocket (or its succession rocket) of JAXA. However, due to the termination of M-V rocket, we are now considering to use HIIA. The orbits of SCOPE satellites are all highly elliptical with its apogee 30Re from the Earth center. The inter-satellite link is used for telemetry/command operation as well as ranging to determine the relative orbits of the 5 satellites in small distances. The SCOPE mission is designed such that observational studies from the new perspective, the crossscale coupling, should be conducted. The orbit of the formation flight are designed such that the spacecraft will visit most of the key regions in the magnetosphere, including the bow shock, the magnetospheric boundary, the inner-magnetosphere, and the near-Earth magnetotail. The key issues for the realization of this mission are: (1) The need for high temporal resolution of electron measurements and quantitative wave field measurements at electron scales; (2) The need for full coverage over the energy range of interests with mass spectroscopy; (3) The need for coordinated space plasma observations by intercommunicated formation flying satellites; and (4) The need to resolve more than one-scale simultaneously. In order to cover the multiple (more than two) scales simultaneously, SCOPE and esa's Cross-Scale have started detailed discussion for the future collaboration. By this collaboration, SCOPE can reduce the number of the daughter satellites that can stay within 100 km throughout the mission life.
NASA Astrophysics Data System (ADS)
Finkenbiner, Catherine; Franz, Trenton E.; Avery, William Alexander; Heeren, Derek M.
2016-04-01
Global trends in consumptive water use indicate a growing and unsustainable reliance on water resources. Approximately 40% of total food production originates from irrigated agriculture. With increasing crop yield demands, water use efficiency must increase to maintain a stable food and water trade. This work aims to increase our understanding of soil hydrologic fluxes at intermediate spatial scales. Fixed and roving cosmic-ray neutron probes were combined in order to characterize the spatial and temporal patterns of soil moisture at three study sites across an East-West precipitation gradient in the state of Nebraska, USA. A coarse scale map was generated for the entire domain (122 km2) at each study site. We used a simplistic data merging technique to produce a statistical daily soil moisture product at a range of key spatial scales in support of current irrigation technologies: the individual sprinkler (˜102m2) for variable rate irrigation, the individual wedge (˜103m2) for variable speed irrigation, and the quarter section (0.82 km2) for uniform rate irrigation. Additionally, we were able to generate a daily soil moisture product over the entire study area at various key modeling and remote sensing scales 12, 32, and 122 km2. Our soil moisture products and derived soil properties were then compared against spatial datasets (i.e. field capacity and wilting point) from the US Department of Agriculture Web Soil Survey. The results show that our "observed" field capacity was higher compared to the Web Soil Survey products. We hypothesize that our results, when provided to irrigators, will decrease water losses due to runoff and deep percolation as sprinkler managers can better estimate irrigation application depth and times in relation to soil moisture depletion below field capacity and above maximum allowable depletion. The incorporation of this non-contact and pragmatic geophysical method into current irrigation practices across the state and globe has the potential to greatly increase agricultural water use efficiency at scale.
Coincident scales of forest feedback on climate and conservation in a diversity hot spot
Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F
2005-01-01
The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest–rainfall feedback at a range of spatial scales from ca 101–104 km2. We show that the strength of the feedback increases up to scales of at least 103 km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 103 km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation. PMID:16608697
Coincident scales of forest feedback on climate and conservation in a diversity hot spot.
Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F
2006-03-22
The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest-rainfall feedback at a range of spatial scales from ca 10(1)-10(4) km2. We show that the strength of the feedback increases up to scales of at least 10(3) km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 10(3) km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation.
NASA Astrophysics Data System (ADS)
D'Alessandro, J.; Diao, M.; Chen, M.
2015-12-01
John D'Alessandro1, Minghui Diao1, Ming Chen2, George Bryan2, Hugh Morrison21. Department of Meteorology and Climate Science, San Jose State University2. Mesoscale & Microscale Meteorology Division, National Center for Atmospheric Research, Boulder, CO, 80301 Ice crystal formation requires the prerequisite condition of ice supersaturation, i.e., relative humidity with respect to ice (RHi) greater than 100%. The formation and evolution of ice supersaturated regions (ISSRs) has large impact on the subsequent formation of ice clouds. To examine the characteristics of simulated ice supersaturated regions at various model spatial resolutions, case studies between airborne in-situ measurements in the NSF Deep Convective, Clouds and Chemistry (DC3) campaign (May - June 2012) and WRF simulations are conducted in this work. Recent studies using ~200 m in-situ observations showed that ice supersaturated regions are mostly around 1 km in horizontal scale (Diao et al. 2014). Yet it is still unclear if such observed characteristics can be represented by WRF simulations at various spatial resolutions. In this work, we compare the WRF simulated anvil cirrus spatial characteristics with those observed in the DC3 campaign over the southern great plains in US. The WRF model is run at 1 km and 3 km horizontal grid spacing with a recent update of Thompson microphysics scheme. Our comparisons focus on the spatial characteristics of ISSRs and cirrus clouds, including the distributions of their horizontal scales, the maximum relative humidity with respect to ice (RHi) and the relationship between RHi and temperature. Our previous work on the NCAR CM1 cloud-resolving model shows that the higher resolution runs (i.e., 250m and 1km) generally have better agreement with observations than the coarser resolution (4km) runs. We will examine if similar trend exists for WRF simulations in deep convection cases. In addition, we will compare the simulation results between WRF and CM1, particularly for spatial correlations between ISSRs and cirrus and their evolution (based on the method of Diao et al. 2013). Overall, our work will help to assess the representation of ISSRs and cirrus in WRF simulation based on comparisons with in-situ observations.
NASA Astrophysics Data System (ADS)
Zhou, J.; Ding, L.
2017-12-01
Land surface air temperature (SAT) is an important parameter in the modeling of radiation balance and energy budget of the earth surface. Generally, SAT is measured at ground meteorological stations; then SAT mapping is possible though a spatial interpolation process. The interpolated SAT map relies on the spatial distribution of ground stations, the terrain, and many other factors; thus, it has great uncertainties in regions with complicated terrain. Instead, SAT map can also be obtained through physical modeling of interactions between the land surface and the atmosphere. Such dataset generally has coarse spatial resolution (e.g. coarser than 0.1°) and cannot satisfy the applications at fine scales, e.g. 1 km. This presentation reports the reconstruction of a three hourly 1-km SAT dataset from 2001 to 2015 over the Qinghai-Tibet Plateau. The terrain in the Qinghai-Tibet Plateau, especially in the eastern part, is extremely complicated. Two SAT datasets with good qualities are used in this study. The first one is from the 3h China Meteorological Forcing Dataset with a 0.1° resolution released by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences (Yang et al., 2010); the second one is from the ERA-Interim product with the same temporal resolution and a 0.125° resolution. A statistical approach is developed to downscale the spatial resolution of the derived SAT to 1-km. The elevation and the normalized difference vegetation index (NDVI) are selected as two scaling factors in the downscaling approach. Results demonstrate there is significantly negative correlation between the SAT and elevation in all seasons; there is also significantly negative correlation between the SAT and NDVI in the vegetation growth seasons, while the correlation decreases in the other seasons. Therefore, a temporally dynamic downscaling approach is feasible to enhance the spatial resolution of the SAT. Compared with the SAT at the 0.1° or 0.125°, the reconstructed 1-km SAT can provide much more spatial details in areas with complicated terrain. Additionally, the 1-km SAT agrees well with the ground measured air temperatures as well as the SAT before downscaling. The reconstructed SAT will be beneficial for the modeling of surface radiation balance and energy budget over the Qinghai-Tibet Plateau.
Peterson, Sarah H.; Lance, Monique M.; Jeffries, Steven J.; Acevedo-Gutiérrez, Alejandro
2012-01-01
Background Worldwide, adult harbor seals (Phoca vitulina) typically limit their movements and activity to <50 km from their primary haul-out site. As a result, the ecological impact of harbor seals is viewed as limited to relatively small spatial scales. Harbor seals in the Pacific Northwest are believed to remain <30 km from their primary haul-out site, one of several contributing factors to the current stock designation. However, movement patterns within the region are not well understood because previous studies have used radio-telemetry, which has range limitations. Our objective was to use satellite-telemetry to determine the regional spatial scale of movements. Methodology/Principal Findings Satellite tags were deployed on 20 adult seals (n=16 males and 4 females) from two rocky reefs and a mudflat-bay during April–May 2007. Standard filtering algorithms were used to remove outliers, resulting in an average (± SD) of 693 (±377) locations per seal over 110 (±32) days. A particle filter was implemented to interpolate locations temporally and decrease erroneous locations on land. Minimum over-water distances were calculated between filtered locations and each seal's capture site to show movement of seals over time relative to their capture site, and we estimated utilization distributions from kernel density analysis to reflect spatial use. Eight males moved >100 km from their capture site at least once, two of which traveled round trip to and from the Pacific coast, a total distance >400 km. Disjunct spatial use patterns observed provide new insight into general harbor seal behavior. Conclusions/Significance Long-distance movements and disjunct spatial use of adult harbor seals have not been reported for the study region and are rare worldwide in such a large proportion of tagged individuals. Thus, the ecological influence of individual seals may reach farther than previously assumed. PMID:22723925
NASA Astrophysics Data System (ADS)
Rosli, Norliana; Leduc, Daniel; Rowden, Ashley A.; Probert, P. Keith; Clark, Malcolm R.
2018-01-01
Deep-sea community attributes vary at a range of spatial scales. However, identifying the scale at which environmental factors affect variability in deep-sea communities remains difficult, as few studies have been designed in such a way as to allow meaningful comparisons across more than two spatial scales. In the present study, we investigated nematode diversity, community structure and trophic structure at different spatial scales (sediment depth (cm), habitat (seamount, canyon, continental slope; 1-100 km), and geographic region (100-10000 km)), while accounting for the effects of water depth, in two regions on New Zealand's continental margin. The greatest variability in community attributes was found between sediment depth layers and between regions, which explained 2-4 times more variability than habitats. The effect of habitat was consistently stronger in the Hikurangi Margin than the Bay of Plenty for all community attributes, whereas the opposite pattern was found in the Bay of Plenty where effect of sediment depth was greater in Bay of Plenty. The different patterns at each scale in each region reflect the differences in the environmental variables between regions that control nematode community attributes. Analyses suggest that nematode communities are mostly influenced by sediment characteristics and food availability, but that disturbance (fishing activity and bioturbation) also accounts for some of the observed patterns. The results provide new insight on the relative importance of processes operating at different spatial scales in regulating nematode communities in the deep-sea, and indicate potential differences in vulnerability to anthropogenic disturbance.
NASA Astrophysics Data System (ADS)
Hirt, Christian; Rexer, Moritz; Scheinert, Mirko; Pail, Roland; Claessens, Sten; Holmes, Simon
2016-02-01
The current high-degree global geopotential models EGM2008 and EIGEN-6C4 resolve gravity field structures to ˜ 10 km spatial scales over most parts of the of Earth's surface. However, a notable exception is continental Antarctica, where the gravity information in these and other recent models is based on satellite gravimetry observations only, and thus limited to about ˜ 80-120 km spatial scales. Here, we present a new degree-2190 global gravity model (GGM) that for the first time improves the spatial resolution of the gravity field over the whole of continental Antarctica to ˜ 10 km spatial scales. The new model called SatGravRET2014 is a combination of recent Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite gravimetry with gravitational signals derived from the 2013 Bedmap2 topography/ice thickness/bedrock model with gravity forward modelling in ellipsoidal approximation. Bedmap2 is a significantly improved description of the topographic mass distribution over the Antarctic region based on a multitude of topographic surveys, and a well-suited source for modelling short-scale gravity signals as we show in our study. We describe the development of SatGravRET2014 which entirely relies on spherical harmonic modelling techniques. Details are provided on the least-squares combination procedures and on the conversion of topography to implied gravitational potential. The main outcome of our work is the SatGravRET2014 spherical harmonic series expansion to degree 2190, and derived high-resolution grids of 3D-synthesized gravity and quasigeoid effects over the whole of Antarctica. For validation, six data sets from the IAG Subcommission 2.4f "Gravity and Geoid in Antarctica" (AntGG) database were used comprising a total of 1,092,981 airborne gravimetric observations. All subsets consistently show that the Bedmap2-based short-scale gravity modelling improves the agreement over satellite-only data considerably (improvement rates ranging between 9 and 75 % with standard deviations from residuals between SatGravRET2014 and AntGG gravity ranging between 8 and 25 mGal). For comparison purposes, a degree-2190 GGM was generated based on the year-2001 Bedmap1 (using the ETOPO1 topography) instead of 2013 Bedmap2 topography product. Comparison of both GGMs against AntGG consistently reveals a closer fit over all test areas when Bedmap2 is used. This experiment provides evidence for clear improvements in Bedmap2 topographic information over Bedmap1 at spatial scales of ˜ 80-10 km, obtained from independent gravity data used as validation tool. As a general conclusion, our modelling effort fills—in approximation—some gaps in short-scale gravity knowledge over Antarctica and demonstrates the value of the Bedmap2 topography data for short-scale gravity refinement in GGMs. SatGravRET2014 can be used, e.g. as a reference model for future gravity modelling efforts over Antarctica, e.g. as foundation for a combination with the AntGG data set to obtain further improved gravity information.
Thrush, Simon F; Hewitt, Judi E; Cummings, Vonda J; Norkko, Alf; Chiantore, Mariachiara
2010-07-30
High Antarctic coastal marine environments are comparatively pristine with strong environmental gradients, which make them important places to investigate biodiversity relationships. Defining how different environmental features contribute to shifts in beta-diversity is especially important as these shifts reflect both spatio-temporal variations in species richness and the degree of ecological separation between local and regional species pools. We used complementary techniques (species accumulation models, multivariate variance partitioning and generalized linear models) to assess how the roles of productivity, bio-physical habitat heterogeneity and connectivity change with spatial scales from metres to 100's of km. Our results demonstrated that the relative importance of specific processes influencing species accumulation and beta-diversity changed with increasing spatial scale, and that patterns were never driven by only one factor. Bio-physical habitat heterogeneity had a strong influence on beta-diversity at scales <290 km, while the effects of productivity were low and significant only at scales >40 km. Our analysis supports the emphasis on the analysis of diversity relationships across multiple spatial scales and highlights the unequal connectivity of individual sites to the regional species pool. This has important implications for resilience to habitat loss and community homogenisation, especially for Antarctic benthic communities where rates of recovery from disturbance are slow, there is a high ratio of poor-dispersing and brooding species, and high biogenic habitat heterogeneity and spatio-temporal variability in primary production make the system vulnerable to disturbance. Consequently, large areas need to be included within marine protected areas for effective management and conservation of these special ecosystems in the face of increasing anthropogenic disturbance.
NASA Astrophysics Data System (ADS)
Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.
2016-05-01
Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.
Peucker, Amanda J.; Valautham, Sureen K.; Styan, Craig A.; Dann, Peter
2015-01-01
Factors responsible for spatial structuring of population genetic variation are varied, and in many instances there may be no obvious explanations for genetic structuring observed, or those invoked may reflect spurious correlations. A study of little penguins (Eudyptula minor) in southeast Australia documented low spatial structuring of genetic variation with the exception of colonies at the western limit of sampling, and this distinction was attributed to an intervening oceanographic feature (Bonney Upwelling), differences in breeding phenology, or sea level change. Here, we conducted sampling across the entire Australian range, employing additional markers (12 microsatellites and mitochondrial DNA, 697 individuals, 17 colonies). The zone of elevated genetic structuring previously observed actually represents the eastern half of a genetic cline, within which structuring exists over much shorter spatial scales than elsewhere. Colonies separated by as little as 27 km in the zone are genetically distinguishable, while outside the zone, homogeneity cannot be rejected at scales of up to 1400 km. Given a lack of additional physical or environmental barriers to gene flow, the zone of elevated genetic structuring may reflect secondary contact of lineages (with or without selection against interbreeding), or recent colonization and expansion from this region. This study highlights the importance of sampling scale to reveal the cause of genetic structuring. PMID:25833231
NASA Astrophysics Data System (ADS)
Loozen, Yasmina; Rebel, Karin T.; Karssenberg, Derek; Wassen, Martin J.; Sardans, Jordi; Peñuelas, Josep; De Jong, Steven M.
2018-05-01
Canopy nitrogen (N) concentration and content are linked to several vegetation processes. Therefore, canopy N concentration is a state variable in global vegetation models with coupled carbon (C) and N cycles. While there are ample C data available to constrain the models, widespread N data are lacking. Remotely sensed vegetation indices have been used to detect canopy N concentration and canopy N content at the local scale in grasslands and forests. Vegetation indices could be a valuable tool to detect canopy N concentration and canopy N content at larger scale. In this paper, we conducted a regional case-study analysis to investigate the relationship between the Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) time series from European Space Agency (ESA) Envisat satellite at 1 km spatial resolution and both canopy N concentration (%N) and canopy N content (N g m-2, of ground area) from a Mediterranean forest inventory in the region of Catalonia, in the northeast of Spain. The relationships between the datasets were studied after resampling both datasets to lower spatial resolutions (20, 15, 10 and 5 km) and at the original spatial resolution of 1 km. The results at higher spatial resolution (1 km) yielded significant log-linear relationships between MTCI and both canopy N concentration and content: r2 = 0.32 and r2 = 0.17, respectively. We also investigated these relationships per plant functional type. While the relationship between MTCI and canopy N concentration was strongest for deciduous broadleaf and mixed plots (r2 = 0.24 and r2 = 0.44, respectively), the relationship between MTCI and canopy N content was strongest for evergreen needleleaf trees (r2 = 0.19). At the species level, canopy N concentration was strongly related to MTCI for European beech plots (r2 = 0.69). These results present a new perspective on the application of MTCI time series for canopy N detection.
Equatorial Density Irregularity Structures at Intermediate Scales and Their Temporal Evolution
NASA Technical Reports Server (NTRS)
Kil, Hyosub; Heelis, R. A.
1998-01-01
We examine high resolution measurements of ion density in the equatorial ionosphere from the AE-E satellite during the years 1977-1981. Structure over spatial scales from 18 km to 200 m is characterized by the spectrum of irregularities at larger and smaller scales and at altitudes above 350 km and below 300 km. In the low-altitude region, only small amplitude large-scale (lambda greater than 5 km) density modulations are often observed, and thus the power spectrum of these density structures exhibits a steep spectral slope at kilometer scales. In the high-altitude region, sinusoidal density fluctuations, characterized by enhanced power near 1-km scale, are frequently observed during 2000-0200 LT. However, such fluctuations are confined to regions at the edges of larger bubble structures where the average background density is high. Small amplitude irregularity structures, observed at early local time hours, grow rapidly to high-intensity structures in about 90 min. Fully developed structures, which are observed at late local time hours, decay very slowly producing only-small differences in spectral characteristics even 4 hours later. The local time evolution of irregularity structure is investigated by using average statistics for low-(1% less than sigma less than 5%) and high-intensity (sigma greater than 10%) structures. At lower altitudes, little chance in the spectral slope is seen as a function of local time, while at higher attitudes the growth and maintenance of structures near 1 km scales dramatically affects the spectral slope.
NASA Astrophysics Data System (ADS)
Pressel, K. G.; Collins, W.; Desai, A. R.
2011-12-01
Deficiencies in the parameterization of boundary layer clouds in global climate models (GCMs) remains one of the greatest sources of uncertainty in climate change predictions. Many GCM cloud parameterizations, which seek to include some representation of subgrid-scale cloud variability, do so by making assumptions regarding the subgrid-scale spatial probability density function (PDF) of total water content. Properly specifying the form and parameters of the total water PDF is an essential step in the formulation of PDF based cloud parameterizations. In the cloud free boundary layer, the PDF of total water mixing ratio is equivalent to the PDF of water vapor mixing ratio. Understanding the PDF of water vapor mixing ratio in the cloud free atmosphere is a necessary step towards understanding the PDF of water vapor in the cloudy atmosphere. A primary challenge in empirically constraining the PDF of water vapor mixing ratio is a distinct lack of a spatially distributed observational dataset at or near cloud scale. However, at meso-beta (20-50km) and larger scales, there is a wealth of information on the spatial distribution of water vapor contained in the physically retrieved water vapor profiles from the Atmospheric Infrared Sounder onboard NASA`s Aqua satellite. The scaling (scale-invariance) of the observed water vapor field has been suggested as means of using observations at satellite observed (meso-beta) scales to derive information about cloud scale PDFs. However, doing so requires the derivation of a robust climatology of water vapor scaling from in-situ observations across the meso- gamma (2-20km) and meso-beta scales. In this work, we present the results of the scaling of high frequency (10Hz) time series of water vapor mixing ratio as observed from the 447m WLEF tower located near Park Falls, Wisconsin. Observations from a tall tower offer an ideal set of observations with which to investigate scaling at meso-gamma and meso-beta scales requiring only the assumption of Taylor`s Hypothesis to convert observed time scales to spatial scales. Furthermore, the WLEF tower holds an instrument suite offering a diverse set of variables at the 396m, 122m, and 30m levels with which to characterize the state of the boundary layer. Three methods are used to compute scaling exponents for the observed time series; poor man`s variance spectra, first order structure functions, and detrended fluctuation analysis. In each case scaling exponents are computed by linear regression. The results for each method are compared and used to build a climatology of scaling exponents. In particular, the results for June 2007 are presented, and it is shown that the scaling of water vapor time series at the 396m level is characterized by two regimes that are determined by the state of the boundary layer. Finally, the results are compared to, and shown to be roughly consistent with, scaling exponents computed from AIRS observations.
NASA Astrophysics Data System (ADS)
Oh, Sungmin; Hohmann, Clara; Foelsche, Ulrich; Fuchsberger, Jürgen; Rieger, Wolfgang; Kirchengast, Gottfried
2017-04-01
WegenerNet Feldbach region (WEGN), a pioneering experiment for weather and climate observations, has recently completed its first 10-year precipitation measurement cycle. The WEGN has measured precipitation, temperature, humidity, and other parameters since the beginning of 2007, supporting local-level monitoring and modeling studies, over an area of about 20 km x 15 km centered near the City of Feldbach (46.93 ˚ N, 15.90 ˚ E) in the Alpine forelands of southeast Austria. All the 151 stations in the network are now equipped with high-quality Meteoservis sensors as of August 2016, following an equipment with Friedrichs sensors at most stations before, and continue to provide high-resolution (2 km2/5-min) gauge based precipitation measurements for interested users in hydro-meteorological communities. Here we will present overall characteristics of the WEGN, with a focus on sub-daily precipitation measurements, from the data processing (data quality control, gridded data products generation, etc.) to data applications (e.g., ground validation of satellite estimates). The latter includes our recent study on the propagation of uncertainty from rainfall to runoff. The study assesses responses of small-catchment runoff to spatial rainfall variability in the WEGN region over the Raab valley, using a physics-based distributed hydrological model; Water Flow and Balance Simulation Model (WaSiM), developed at ETH Zurich (Schulla, ETH Zurich, 1997). Given that uncertainty due to resolution of rainfall measurements is believed to be a significant source of error in hydrologic modeling especially for convective rainfall that dominates in the region during summer, the high-resolution of WEGN data furnishes a great opportunity to analyze effects of rainfall events on the runoff at different spatial resolutions. Furthermore, the assessment can be conducted not only for the lower Raab catchment (area of about 500 km2) but also for its sub-catchments (areas of about 30-70 km2). Beside the question how many stations are necessary for reliable hydrological modeling, different interpolation methods like Inverse Distance Interpolation, Elevation Dependent Regression, and combinations will be tested. This presentation will show the first results from a scale-depending analysis of spatial and temporal structures of heavy rainfall events and responses of simulated runoff at the event scale in the WEGN region.
NASA Astrophysics Data System (ADS)
Vachula, R. S.; Huang, Y.; Russell, J. M.
2017-12-01
Lake sediment-based fire reconstructions offer paleoenvironmental context in which to assess modern fires and predict future burning. However, despite the ubiquity, many uncertainties remain regarding the taphonomy of paleofire proxies and the spatial scales for which they record variations in fire history. Here we present down-core proxy analyses of polycyclic aromatic hydrocarbons (PAHs) and three size-fractions of charcoal (63-150, >150 and >250 μm) from Swamp Lake, California, an annually laminated lacustrine archive. Using a statewide historical GIS dataset of area burned, we assess the spatial scales for which these proxies are reliable recorders of fire history. We find that the coherence of observed and proxy-recorded fire history inherently depends upon spatial scale. Contrary to conventional thinking that charcoal mainly records local fires, our results indicate that macroscopic charcoal (>150 μm) may record spatially broader (<25 km) changes in fire history, and as such, the coarsest charcoal particles (>250 μm) may be a more conservative proxy for local burning. We find that sub-macroscopic charcoal particles (63-150 μm) reliably record regional (up to 150 km) changes in fire history. These results indicate that charcoal-based fire reconstructions may represent spatially broader fire history than previously thought, which has major implications for our understanding of spatiotemporal paleofire variations. Our analyses of PAHs show that dispersal mobility is heterogeneous between compounds, but that PAH fluxes are reliable proxies of fire history within 25-50 km, which suggests PAHs may be a better spatially constrained paleofire proxy than sedimentary charcoal. Further, using a linear discriminant analysis model informed by modern emissions analyses, we show that PAH assemblages preserved in lake sediments can differentiate vegetation type burned, and are thus promising paleoecological biomarkers warranting further research and implementation. In sum, our analyses offer new insight into the spatial dimensions of paleofire proxies and constitute a methodology that can be applied to other locations and proxies to better inform site-specific reconstructions.
Beatty, William S.; Webb, Elisabeth B.; Kesler, Dylan C.; Raedeke, Andrew H.; Naylor, Luke W.; Humburg, Dale D.
2014-01-01
Previous studies that evaluated effects of landscape-scale habitat heterogeneity on migratory waterbird distributions were spatially limited and temporally restricted to one major life-history phase. However, effects of landscape-scale habitat heterogeneity on long-distance migratory waterbirds can be studied across the annual cycle using new technologies, including global positioning system satellite transmitters. We used Bayesian discrete choice models to examine the influence of local habitats and landscape composition on habitat selection by a generalist dabbling duck, the mallard (Anas platyrhynchos), in the midcontinent of North America during the non-breeding period. Using a previously published empirical movement metric, we separated the non-breeding period into three seasons, including autumn migration, winter, and spring migration. We defined spatial scales based on movement patterns such that movements >0.25 and <30.00 km were classified as local scale and movements >30.00 km were classified as relocation scale. Habitat selection at the local scale was generally influenced by local and landscape-level variables across all seasons. Variables in top models at the local scale included proximities to cropland, emergent wetland, open water, and woody wetland. Similarly, variables associated with area of cropland, emergent wetland, open water, and woody wetland were also included at the local scale. At the relocation scale, mallards selected resource units based on more generalized variables, including proximity to wetlands and total wetland area. Our results emphasize the role of landscape composition in waterbird habitat selection and provide further support for local wetland landscapes to be considered functional units of waterbird conservation and management.
NASA Astrophysics Data System (ADS)
Schoch, Anna; Blöthe, Jan; Hoffmann, Thomas; Schrott, Lothar
2016-04-01
A large number of sediment budgets have been compiled on different temporal and spatial scales in alpine regions. Detailed sediment budgets based on the quantification of a number of sediment storages (e.g. talus cones, moraine deposits) exist only for a few small scale drainage basins (up to 10² km²). In contrast, large scale sediment budgets (> 10³ km²) consider only long term sediment sinks such as valley fills and lakes. Until now, these studies often neglect small scale sediment storages in the headwaters. However, the significance of these sediment storages have been reported. A quantitative verification whether headwaters function as sediment source regions is lacking. Despite substantial transport energy in mountain environments due to steep gradients and high relief, sediment flux in large river systems is frequently disconnected from alpine headwaters. This leads to significant storage of coarse-grained sediment along the flow path from rockwall source regions to large sedimentary sinks in major alpine valleys. To improve the knowledge on sediment budgets in large scale alpine catchments and to bridge the gap between small and large scale sediment budgets, we apply a multi-method approach comprising investigations on different spatial scales in the Upper Rhone Basin (URB). The URB is the largest inneralpine basin in the European Alps with a size of > 5400 km². It is a closed system with Lake Geneva acting as an ultimate sediment sink for suspended and clastic sediment. We examine the spatial pattern and volumes of sediment storages as well as the morphometry on the local and catchment-wide scale. We mapped sediment storages and bedrock in five sub-regions of the study area (Goms, Lötschen valley, Val d'Illiez, Vallée de la Liène, Turtmann valley) in the field and from high-resolution remote sensing imagery to investigate the spatial distribution of different sediment storage types (e.g. talus deposits, debris flow cones, alluvial fans). These sub-regions cover all three litho-tectonic units of the URB (Helvetic nappes, Penninic nappes, External massifs) and different catchment sizes to capture the inherent variability. Different parameters characterizing topography, surface characteristics, and vegetation cover are analyzed for each storage type. The data is then used in geostatistical models (PCA, stepwise logistic regression) to predict the spatial distribution of sediment storage for the whole URB. We further conduct morphometric analyses of the URB to gain information on the varying degree of glacial imprint and postglacial landscape evolution and their control on the spatial distribution of sediment storage in a large scale drainage basin. Geophysical methods (ground penetrating radar and electrical resistivity tomography) are applied on different sediment storage types on the local scale to estimate mean thicknesses. Additional data from published studies are used to complement our dataset. We integrate the local data in the statistical model on the spatial distribution of sediment storages for the whole URB. Hence, we can extrapolate the stored sediment volumes to the regional scale in order to bridge the gap between small and large scale studies.
NASA Astrophysics Data System (ADS)
Schoch, Anna; Blöthe, Jan Henrik; Hoffmann, Thomas; Schrott, Lothar
2018-02-01
There is a notable discrepancy between detailed sediment budget studies in small headwater catchments (< 102 km2) focusing on the identification of sedimentary landforms in the field (e.g. talus cones, moraine deposits, fans) and large scale studies (> 103 km2) in higher order catchments applying modeling and/or remote sensing based approaches for major sediment storage delineation. To bridge the gap between these scales, we compiled an inventory of sediment and bedrock coverage from field mapping, remote sensing analysis and published data for five key sites in the Upper Rhone Basin (Val d'Illiez, Val de la Liène, Turtmanntal, Lötschental, Goms; 360.3 km2, equivalent to 6.7% of the Upper Rhone Basin). This inventory was used as training and testing data for the classification of sediment and bedrock cover. From a digital elevation model (2 × 2 m ground resolution) and Landsat imagery we derived 22 parameters characterizing local morphometry, topography and position, contributing area, and climatic and biotic factors on different spatial scales, which were used as inputs for different statistical models (logistic regression, principal component logistic regression, generalized additive model). Best prediction results with an excellent performance (mean AUROC: 0.8721 ± 0.0012) and both a high spatial and non-spatial transferability were achieved applying a generalized additive model. Since the model has a high thematic consistency, the independent input variables chosen based on their geomorphic relevance are suitable to model the spatial distribution of sediment. Our high-resolution classification shows that 53.5 ± 21.7% of the Upper Rhone Basin are covered with sediment. These are by no means evenly distributed: small headwaters (< 5 km2) feature a very strong variability in sediment coverage, with watersheds drowning in sediments juxtaposed to watersheds devoid of sediment cover. In contrast, larger watersheds predominantly show a bimodal distribution, with highest densities for bedrock (30-40%) being consistently lower than for sediment cover (60-65%). Earlier studies quantifying sedimentary cover and volume focus on the broad glacially overdeepened Rhone Valley that accounts for c. 9% of our study area. While our data support its importance, we conservatively estimate that the remaining 90% of sediment cover, mainly located outside trunk valleys, account for a volume of 2.6-13 km3, i.e. 2-16% of the estimated sediment volume stored in the Rhone Valley between Brig and Lake Geneva. Furthermore, our data reveal increased relative sediment cover in areas deglaciated since the Little Ice Age, as compared to headwater regions without this recent glacial imprint. We therefore conclude that sediment storage in low-order valleys, often neglected in large scale studies, constitutes a significant component of large scale sediment budgets that needs to be better included into future analysis.
Spatial Representativeness of Surface-Measured Variations of Downward Solar Radiation
NASA Astrophysics Data System (ADS)
Schwarz, M.; Folini, D.; Hakuba, M. Z.; Wild, M.
2017-12-01
When using time series of ground-based surface solar radiation (SSR) measurements in combination with gridded data, the spatial and temporal representativeness of the point observations must be considered. We use SSR data from surface observations and high-resolution (0.05°) satellite-derived data to infer the spatiotemporal representativeness of observations for monthly and longer time scales in Europe. The correlation analysis shows that the squared correlation coefficients (R2) between SSR times series decrease linearly with increasing distance between the surface observations. For deseasonalized monthly mean time series, R2 ranges from 0.85 for distances up to 25 km between the stations to 0.25 at distances of 500 km. A decorrelation length (i.e., the e-folding distance of R2) on the order of 400 km (with spread of 100-600 km) was found. R2 from correlations between point observations and colocated grid box area means determined from satellite data were found to be 0.80 for a 1° grid. To quantify the error which arises when using a point observation as a surrogate for the area mean SSR of larger surroundings, we calculated a spatial sampling error (SSE) for a 1° grid of 8 (3) W/m2 for monthly (annual) time series. The SSE based on a 1° grid, therefore, is of the same magnitude as the measurement uncertainty. The analysis generally reveals that monthly mean (or longer temporally aggregated) point observations of SSR capture the larger-scale variability well. This finding shows that comparing time series of SSR measurements with gridded data is feasible for those time scales.
Small-scale heterogeneity spectra in the Earth mantle resolved by PKP-ab,-bc and -df waves
NASA Astrophysics Data System (ADS)
Zheng, Y.
2016-12-01
Plate tectonics creates heterogeneities at mid ocean ridges and subducts the heterogeneities back to the mantle at subduction zones. Heterogeneities manifest themselves by different densities and seismic wave speeds. The length scales and spatial distribution of the heterogeneities measure the mixing mechanism of the plate tectonics. This information can be mathematically captured as the heterogeneity spatial Fourier spectrum. Since most heterogeneities created are on the order of 10s of km, global seismic tomography is not able to resolve them directly. Here, we use seismic P-waves that transmit through the outer core (phases: PKP-ab and PKP-bc) and through the inner core (PKP-df) to probe the lower-mantle heterogeneities. The differential traveltimes (PKP-ab versus PKP-df; PKP-bc versus PKP-df) are sensitive to lower mantle structures. We have collected more than 10,000 PKP phases recorded by Japan Hi-Net short-period seismic network. We found that the lower mantle was filled with seismic heterogeneities from scale 20km to 200km. The heterogeneity spectrum is similar to an exponential distribution but is more enriched in small-scale heterogeneities at the high-wavenumber end. The spectrum is "red" meaning large scales have more power and heterogeneities show a multiscale nature: small-scale heterogeneities are embedded in large-scale heterogeneities. These small-scale heterogeneities cannot be due to thermal origin and they must be compositional. If all these heterogeneities were located in the D" layer, statistically, it would have a root-mean-square P-wave velocity fluctuation of 1% (i.e., -3% to 3%).
A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning
NASA Astrophysics Data System (ADS)
Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid
2016-04-01
Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.
Uranium and radon in private bedrock well water in Maine: geospatial analysis at two scales
Yang, Qiang; Smitherman, Paul; Hess, C.T.; Culbertson, Charles W.; Marvinney, Robert G.; Zheng, Yan
2014-01-01
In greater Augusta of central Maine, 53 out of 1093 (4.8%) private bedrock well water samples from 1534 km2 contained [U] >30 μg/L, the U.S. Environmental Protection Agency’s (EPA) Maximum Contaminant Level (MCL) for drinking water; and 226 out of 786 (29%) samples from 1135 km2 showed [Rn] >4,000 pCi/L (148 Bq/L), the U.S. EPA’s Alternative MCL. Groundwater pH, calcite dissolution and redox condition are factors controlling the distribution of groundwater U but not Rn due to their divergent chemical and hydrological properties. Groundwater U is associated with incompatible elements (S, As, Mo, F, and Cs) in water samples within granitic intrusions. Elevated [U] and [Rn] are located within 5–10 km distance of granitic intrusions but do not show correlations with metamorphism at intermediate scales (100−101 km). This spatial association is confirmed by a high-density sampling (n = 331, 5–40 samples per km2) at local scales (≤10–1 km) and the statewide sampling (n = 5857, 1 sample per 16 km2) at regional scales (102–103 km). Wells located within 5 km of granitic intrusions are at risk of containing high levels of [U] and [Rn]. Approximately 48 800–63 900 and 324 000 people in Maine are estimated at risk of exposure to U (>30 μg/L) and Rn (>4000 pCi/L) in well water, respectively.
Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre
2015-01-01
Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate “wall-to-wall” remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution. PMID:26402522
NASA Astrophysics Data System (ADS)
Comas, X.; Wright, W. J.; Hynek, S. A.; Ntarlagiannis, D.; Terry, N.; Job, M. J.; Fletcher, R. C.; Brantley, S.
2017-12-01
Previous studies in the Rio Icacos watershed in the Luquillo Mountains (Puerto Rico) have shown that regolith materials are rapidly developed from the alteration of quartz diorite bedrock, and create a blanket on top of the bedrock with a thickness that decreases with proximity to the knickpoint. The watershed is also characterized by a system of heterogeneous fractures that likely drive bedrock weathering and the formation of corestones and associated spheroidal fracturing and rindlets. Previous efforts to characterize the spatial distribution of fractures were based on aerial images that did not account for the architecture of the critical zone below the subsurface. In this study we use an array of near-surface geophysical methods at multiple scales to better understand how the spatial distribution and density of fractures varies with topography and proximity to the knickpoint. Large km-scale surveys using ground penetrating radar (GPR), terrain conductivity, and capacitively coupled resistivity, were combined with smaller scale surveys (10-100 m) using electrical resistivity imaging (ERI), and shallow seismics, and were directly constrained with boreholes from previous studies. Geophysical results were compared to theoretical models of compressive stress as due to gravity and regional compression, and showed consistency at describing increased dilation of fractures with proximity to the knickpoint. This study shows the potential of multidisciplinary approaches to model critical zone processes at multiple scales of measurement and high spatial resolution. The approach can be particularly efficient at large km-scales when applying geophysical methods that allow for rapid data acquisition (i.e. walking pace) at high spatial resolution (i.e. cm scales).
Does Fire Influence the Landscape-Scale Distribution of an Invasive Mesopredator?
Payne, Catherine J.; Ritchie, Euan G.; Kelly, Luke T.; Nimmo, Dale G.
2014-01-01
Predation and fire shape the structure and function of ecosystems globally. However, studies exploring interactions between these two processes are rare, especially at large spatial scales. This knowledge gap is significant not only for ecological theory, but also in an applied context, because it limits the ability of landscape managers to predict the outcomes of manipulating fire and predators. We examined the influence of fire on the occurrence of an introduced and widespread mesopredator, the red fox (Vulpes vulpes), in semi-arid Australia. We used two extensive and complimentary datasets collected at two spatial scales. At the landscape-scale, we surveyed red foxes using sand-plots within 28 study landscapes – which incorporated variation in the diversity and proportional extent of fire-age classes – located across a 104 000 km2 study area. At the site-scale, we surveyed red foxes using camera traps at 108 sites stratified along a century-long post-fire chronosequence (0–105 years) within a 6630 km2 study area. Red foxes were widespread both at the landscape and site-scale. Fire did not influence fox distribution at either spatial scale, nor did other environmental variables that we measured. Our results show that red foxes exploit a broad range of environmental conditions within semi-arid Australia. The presence of red foxes throughout much of the landscape is likely to have significant implications for native fauna, particularly in recently burnt habitats where reduced cover may increase prey species’ predation risk. PMID:25291186
NASA Astrophysics Data System (ADS)
Fu, Lee-Lueng; Morrow, Rosemary
2016-07-01
The global observations of the sea surface height (SSH) have revolutionized oceanography since the beginning of precision radar altimetry in the early 1990s. For the first time we have continuous records of SSH with spatial and temporal sampling for detecting the global mean sea level rise, the waxing and waning of El Niño, and the ocean circulation from gyres to ocean eddies. The limit of spatial resolution of the present constellation of radar altimeters in mapping SSH variability is approaching 100 km (in wavelength) with 3 or more simultaneous altimetric satellites in orbit. At scales shorter than 100 km, the circulation contains substantial amount of kinetic energy in currents, eddies and fronts that are responsible for the stirring and mixing of the ocean, especially from the vertical exchange of the upper ocean with the deep. A mission currently in development will use the technique of radar interferometry for making high-resolution measurement of the height of water over the ocean as well as on land. It is called Surface Water and Ocean Topography (SWOT), which is a joint mission of US NASA and French CNES, with contributions from Canada and UK. SWOT promises the detection of SSH at scales approaching 15 km, depending on the sea state. SWOT will make SSH measurement over a swath of 120 km with a nadir gap of 20 km in a 21-day repeat orbit. A conventional radar altimeter will provide measurement along the nadir. This is an exploratory mission with applications in oceanography and hydrology. The increased spatial resolution offers an opportunity to study ocean surface processes to address important questions about the ocean circulation. However, the limited temporal sampling poses challenges to map the evolution of the ocean variability that changes rapidly at the small scales. The measurement technique and the development of the mission will be presented with emphasis on its science program with outlook on the opportunities and challenges.
Ferrell, A Michelle; Brinkerhoff, R Jory
2018-04-12
Patterns of vector-borne disease risk are changing globally in space and time and elevated disease risk of vector-borne infection can be driven by anthropogenic modification of the environment. Incidence of Lyme disease, caused by the bacterium Borrelia burgdorferi sensu stricto, has risen in a number of locations in North America and this increase may be driven by spatially or numerically expanding populations of the primary tick vector, Ixodes scapularis . We used a model selection approach to identify habitat fragmentation and land-use/land cover variables to test the hypothesis that the amount and configuration of forest cover at spatial scales relevant to deer, the primary hosts of adult ticks, would be the predominant determinants of tick abundance. We expected that land cover heterogeneity and amount of forest edge, a habitat thought to facilitate deer foraging and survival, would be the strongest driver of tick density and that larger spatial scales (5-10 km) would be more important than smaller scales (1 km). We generated metrics of deciduous and mixed forest fragmentation using Fragstats 4.4 implemented in ArcMap 10.3 and found, after adjusting for multicollinearity, that total forest edge within a 5 km buffer had a significant negative effect on tick density and that the proportion of forested land cover within a 10 km buffer was positively associated with density of I. scapularis nymphs. None of the 1 km fragmentation metrics were found to significantly improve the fit of the model. Elevation, previously associated with increased density of I. scapularis nymphs in Virginia, while significantly predictive in univariate analysis, was not an important driver of nymph density relative to fragmentation metrics. Our results suggest that amount of forest cover (i.e., lack of fragmentation) is the most important driver of I. scapularis density in our study system.
Performance of the Multi-Radar Multi-Sensor System over the Lower Colorado River, Texas
NASA Astrophysics Data System (ADS)
Bayabil, H. K.; Sharif, H. O.; Fares, A.; Awal, R.; Risch, E.
2017-12-01
Recently observed increases in intensities and frequencies of climate extremes (e.g., floods, dam failure, and overtopping of river banks) necessitate the development of effective disaster prevention and mitigation strategies. Hydrologic models can be useful tools in predicting such events at different spatial and temporal scales. However, accuracy and prediction capability of such models are often constrained by the availability of high-quality representative hydro-meteorological data (e.g., precipitation) that are required to calibrate and validate such models. Improved technologies and products such as the Multi-Radar Multi-Sensor (MRMS) system that allows gathering and transmission of vast meteorological data have been developed to provide such data needs. While the MRMS data are available with high spatial and temporal resolutions (1 km and 15 min, respectively), its accuracy in estimating precipitation is yet to be fully investigated. Therefore, the main objective of this study is to evaluate the performance of the MRMS system in effectively capturing precipitation over the Lower Colorado River, Texas using observations from a dense rain gauge network. In addition, effects of spatial and temporal aggregation scales on the performance of the MRMS system were evaluated. Point scale comparisons were made at 215 gauging locations using rain gauges and MRMS data from May 2015. Moreover, the effects of temporal and spatial data aggregation scales (30, 45, 60, 75, 90, 105, and 120 min) and (4 to 50 km), respectively on the performance of the MRMS system were tested. Overall, the MRMS system (at 15 min temporal resolution) captured precipitation reasonably well, with an average R2 value of 0.65 and RMSE of 0.5 mm. In addition, spatial and temporal data aggregations resulted in increases in R2 values. However, reduction in RMSE was achieved only with an increase in spatial aggregations.
A planktonic diatom displays genetic structure over small spatial scales.
Sefbom, Josefin; Kremp, Anke; Rengefors, Karin; Jonsson, Per R; Sjöqvist, Conny; Godhe, Anna
2018-04-03
Marine planktonic microalgae have potentially global dispersal, yet reduced gene flow has been confirmed repeatedly for several species. Over larger distances (>200 km) geographic isolation and restricted oceanographic connectivity have been recognized as instrumental in driving population divergence. Here we investigated whether similar patterns, that is, structured populations governed by geographic isolation and/or oceanographic connectivity, can be observed at smaller (6-152 km) geographic scales. To test this we established 425 clonal cultures of the planktonic diatom Skeletonema marinoi collected from 11 locations in the Archipelago Sea (northern Baltic Sea). The region is characterized by a complex topography, entailing several mixing regions of which four were included in the sampling area. Using eight microsatellite markers and conventional F-statistics, significant genetic differentiation was observed between several sites. Moreover, Bayesian cluster analysis revealed the co-occurrence of two genetic groups spread throughout the area. However, geographic isolation and oceanographic connectivity could not explain the genetic patterns observed. Our data reveal hierarchical genetic structuring whereby despite high dispersal potential, significantly diverged populations have developed over small spatial scales. Our results suggest that biological characteristics and historical events may be more important in generating barriers to gene flow than physical barriers at small spatial scales. © 2018 Society for Applied Microbiology and John Wiley & Sons Ltd.
Assessing Habitat Suitability at Multiple Scales: A Landscape-Level Approach
Kurt H. Riitters; R.V. O' Neill; K.B. Jones
1997-01-01
The distribution and abundance of many plants and animals are influenced by the spatial arrangement of suitable habitats across landscapes. We derived habitat maps from a digital land cover map of the ~178,000 km2 Chesapeake Bay Watershed by using a spatial filtering algorithm. The regional amounts and patterns of habitats were different for...
Spatial Analysis of Rice Blast in China at Three Different Scales.
Guo, Fangfang; Chen, Xinglong; Lu, Minghong; Yang, Li; Wang, Shi Wei; Wu, Bo Ming
2018-05-22
In this study, spatial analyses were conducted at three different scales to better understand the epidemiology of rice blast, a major rice disease caused by Magnaporthe oryzae. At regional scale, across the major rice production regions in China, rice blast incidence was monitored on 101 dates at 193 stations from June 10 th to Sep. 10 th during 2009-2014, and surveyed in 143 fields in September, 2016; at county scale, 3 surveys were done covering 1-5 counties in 2015-2016; and at field scale, blast was evaluated in 6 fields in 2015-2016. Spatial cluster and hot spot analyses were conducted in GIS on the geographical pattern of the disease at regional scale, and geostatistical analysis performed at all the three scales. Cluster and hot spot analyses revealed that high-disease areas were clustered in mountainous areas in China. Geostatistical analyses detected spatial dependence of blast incidence with influence ranges of 399 to 1080 km at regional scale, and 5 to 10 m at field scale, but not at county scale. The spatial patterns at different scales might be determined by inherent properties of rice blast and environmental driving forces, and findings from this study provide helpful information to sampling and management of rice blast.
NASA Astrophysics Data System (ADS)
Krietemeyer, Andreas; ten Veldhuis, Marie-claire; van de Giesen, Nick
2017-04-01
Recent research has shown that assimilation of Precipitable Water Vapor (PWV) measurements into numerical weather predictions models improve the quality of rainfall now- and forecasting. Local PWV fluctuations may be related with water vapor increases in the lower troposphere which lead to deep convection. Prior studies show that about 20 minutes before rain occurs, the amount of water vapor in the atmosphere at 1 km height increases. Monitoring the small-scale temporal and spatial variability of PWV is therefore crucial to improve the weather now- and forecasting for convective storms, that are typically critical for urban stormwater systems. One established technique to obtain PWV measurements in the atmosphere is to exploit signal delays from GNSS satellites to dual-frequency receivers on the ground. Existing dual-frequency receiver networks typically have inter-station distances in the order of tens of kilometers, which is not sufficiently dense to capture the small-scale PWV variations. In this study, we will add low-cost, single-frequency GNSS receivers to an existing dual-frequency receiver network to obtain an inter-station distance of about 1 km in the Rotterdam area (Netherlands). The aim is to investigate the spatial variability of PWV in the atmosphere at this scale. We use the surrounding dual-frequency network (distributed over a radius of approximately 25 km) to apply an ionospheric delay model that accounts for the delay in the ionosphere (50-1000 km altitude) that cannot be eliminated by single-frequency receivers. The results are validated by co-aligning a single-frequency receiver to a dual-frequency receiver. In the next steps, we will investigate how the high temporal and increased spatial resolution network can help to improve high-resolution rainfall forecasts. Their supposed improved forecasting results will be evaluated based on high-resolution rainfall estimates from a polarimetric X-band rainfall radar installed in the city of Rotterdam.
A new gridded on-road CO2 emissions inventory for the United States, 1980-2011
NASA Astrophysics Data System (ADS)
Gately, C.; Hutyra, L.; Sue Wing, I.
2013-12-01
On-road transportation is responsible for 28% of all U.S. fossil fuel CO2 emissions. However, mapping vehicle emissions at regional scales is challenging due to data limitations. Existing emission inventories have used spatial proxies such as population and road density to downscale national or state level data, which may introduce errors where the proxy variables and actual emissions are weakly correlated. We have developed a national on-road emissions inventory product based on roadway-level traffic data obtained from the Highway Performance Monitoring System. We produce annual estimates of on-road CO2 emissions at a 1km spatial resolution for the contiguous United States for the years 1980 through 2011. For the year 2011 we also produce an hourly emissions product at the 1km scale using hourly traffic volumes from hundreds of automated traffic counters across the country. National on-road emissions rose at roughly 2% per year from 1980 to 2006, with emissions peaking at 1.71 Tg CO2 in 2007. However, while national emissions have declined 6% since the peak, we observe considerable regional variation in emissions trends post-2007. While many states show stable or declining on-road emissions, several states and metropolitan areas in the Midwest, mountain west and south had emissions increases of 3-10% from 2008 to 2011. Our emissions estimates are consistent with state-reported totals of gasoline and diesel fuel consumption. This is in contrast to on-road CO2 emissions estimated by the Emissions Database of Global Atmospheric Research (EDGAR), which we show to be inconsistent in matching on-road emissions to published fuel consumption at the scale of U.S. states, due to the non-linear relationships between emissions and EDGAR's chosen spatial proxies at these scales. Since our emissions estimates were generated independent of population density and other demographic data, we were able to conduct a panel regression analysis to estimate the relationship between these variables and on-road CO2 at various spatial scales. In the case of Massachusetts we find a non-linear relationship between emissions and population density indicating that increasing density resulted in increased emissions when density is less than 2000 persons-km-2. These results highlight the value of using an emissions inventory with high spatial and temporal resolution. At coarser spatial scales, much of the variation in population density and on-road emissions between towns is lost due to aggregation. The high spatial resolution and broad temporal scope of our CO2 estimates provides a basis for analyses to support emissions monitoring, verification and mitigation policies at regional, state and local scale.
Saranya, K R L; Reddy, C Sudhakar; Rao, P V V Prasada; Jha, C S
2014-05-01
Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004-2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km(2). There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km(2) (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km(2) is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km(2)) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.
Developing particle emission inventories using remote sensing (PEIRS).
Tang, Chia-Hsi; Coull, Brent A; Schwartz, Joel; Lyapustin, Alexei I; Di, Qian; Koutrakis, Petros
2017-01-01
Information regarding the magnitude and distribution of PM 2.5 emissions is crucial in establishing effective PM regulations and assessing the associated risk to human health and the ecosystem. At present, emission data is obtained from measured or estimated emission factors of various source types. Collecting such information for every known source is costly and time-consuming. For this reason, emission inventories are reported periodically and unknown or smaller sources are often omitted or aggregated at large spatial scale. To address these limitations, we have developed and evaluated a novel method that uses remote sensing data to construct spatially resolved emission inventories for PM 2.5 . This approach enables us to account for all sources within a fixed area, which renders source classification unnecessary. We applied this method to predict emissions in the northeastern United States during the period 2002-2013 using high-resolution 1 km × 1 km aerosol optical depth (AOD). Emission estimates moderately agreed with the EPA National Emission Inventory (R 2 = 0.66-0.71, CV = 17.7-20%). Predicted emissions are found to correlate with land use parameters, suggesting that our method can capture emissions from land-use-related sources. In addition, we distinguished small-scale intra-urban variation in emissions reflecting distribution of metropolitan sources. In essence, this study demonstrates the great potential of remote sensing data to predict particle source emissions cost-effectively. We present a novel method, particle emission inventories using remote sensing (PEIRS), using remote sensing data to construct spatially resolved PM 2.5 emission inventories. Both primary emissions and secondary formations are captured and predicted at a high spatial resolution of 1 km × 1 km. Using PEIRS, large and comprehensive data sets can be generated cost-effectively and can inform development of air quality regulations.
The Europa Imaging System (EIS): Investigating Europa's geology, ice shell, and current activity
NASA Astrophysics Data System (ADS)
Turtle, Elizabeth; Thomas, Nicolas; Fletcher, Leigh; Hayes, Alexander; Ernst, Carolyn; Collins, Geoffrey; Hansen, Candice; Kirk, Randolph L.; Nimmo, Francis; McEwen, Alfred; Hurford, Terry; Barr Mlinar, Amy; Quick, Lynnae; Patterson, Wes; Soderblom, Jason
2016-07-01
NASA's Europa Mission, planned for launch in 2022, will perform more than 40 flybys of Europa with altitudes at closest approach as low as 25 km. The instrument payload includes the Europa Imaging System (EIS), a camera suite designed to transform our understanding of Europa through global decameter-scale coverage, topographic and color mapping, and unprecedented sub- meter-scale imaging. EIS combines narrow-angle and wide-angle cameras to address these science goals: • Constrain the formation processes of surface features by characterizing endogenic geologic structures, surface units, global cross-cutting relationships, and relationships to Europa's subsurface structure and potential near-surface water. • Search for evidence of recent or current activity, including potential plumes. • Characterize the ice shell by constraining its thickness and correlating surface features with subsurface structures detected by ice penetrating radar. • Characterize scientifically compelling landing sites and hazards by determining the nature of the surface at scales relevant to a potential lander. EIS Narrow-angle Camera (NAC): The NAC, with a 2.3°° x 1.2°° field of view (FOV) and a 10-μμrad instantaneous FOV (IFOV), achieves 0.5-m pixel scale over a 2-km-wide swath from 50-km altitude. A 2-axis gimbal enables independent targeting, allowing very high-resolution stereo imaging to generate digital topographic models (DTMs) with 4-m spatial scale and 0.5-m vertical precision over the 2-km swath from 50-km altitude. The gimbal also makes near-global (>95%) mapping of Europa possible at ≤50-m pixel scale, as well as regional stereo imaging. The NAC will also perform high-phase-angle observations to search for potential plumes. EIS Wide-angle Camera (WAC): The WAC has a 48°° x 24°° FOV, with a 218-μμrad IFOV, and is designed to acquire pushbroom stereo swaths along flyby ground-tracks. From an altitude of 50 km, the WAC achieves 11-m pixel scale over a 44-km-wide swath, generating DTMs with 32-m spatial scale and 4-m vertical precision. These data also support characterization of surface clutter for interpretation of radar deep and shallow sounding modes. Detectors: The cameras have identical rapid-readout, radiation-hard 4k x 2k CMOS detectors and can image in both pushbroom and framing modes. Color observations are acquired by pushbroom imaging using six broadband filters (~300-1050 nm), allowing mapping of surface units for correlation with geologic structures, topography, and compositional units from other instruments.
Jathanna, Devcharan; Karanth, K. Ullas; Kumar, N. Samba; Karanth, Krithi K.; Goswami, Varun R.
2015-01-01
Understanding species distribution patterns has direct ramifications for the conservation of endangered species, such as the Asian elephant Elephas maximus. However, reliable assessment of elephant distribution is handicapped by factors such as the large spatial scales of field studies, survey expertise required, the paucity of analytical approaches that explicitly account for confounding observation processes such as imperfect and variable detectability, unequal sampling probability and spatial dependence among animal detections. We addressed these problems by carrying out ‘detection—non-detection’ surveys of elephant signs across a c. 38,000-km2 landscape in the Western Ghats of Karnataka, India. We analyzed the resulting sign encounter data using a recently developed modeling approach that explicitly addresses variable detectability across space and spatially dependent non-closure of occupancy, across sampling replicates. We estimated overall occupancy, a parameter useful to monitoring elephant populations, and examined key ecological and anthropogenic drivers of elephant presence. Our results showed elephants occupied 13,483 km2 (SE = 847 km2) corresponding to 64% of the available 21,167 km2 of elephant habitat in the study landscape, a useful baseline to monitor future changes. Replicate-level detection probability ranged between 0.56 and 0.88, and ignoring it would have underestimated elephant distribution by 2116 km2 or 16%. We found that anthropogenic factors predominated over natural habitat attributes in determining elephant occupancy, underscoring the conservation need to regulate them. Human disturbances affected elephant habitat occupancy as well as site-level detectability. Rainfall is not an important limiting factor in this relatively humid bioclimate. Finally, we discuss cost-effective monitoring of Asian elephant populations and the specific spatial scales at which different population parameters can be estimated. We emphasize the need to model the observation and sampling processes that often obscure the ecological process of interest, in this case relationship between elephants to their habitat. PMID:26207378
Distributions of soil phosphorus in China's densely populated village landscapes
Jiaguo Jiao; Erle C. Ellis; Ian Yesilonis; Junxi Wu; Hongqing Wang; Huixin Li; Linzhang Yang
2010-01-01
Purpose Village landscapes, which integrate small-scale agriculture with housing, forestry and a host of other land use practices, cover more than 2x106 km2 across China. Village lands tend to be managed at very fine spatial scales (≤30 m), with managers altering soil fertility and even terrain by terracing,...
Large-scale phenomena, chapter 3, part D
NASA Technical Reports Server (NTRS)
1975-01-01
Oceanic phenomena with horizontal scales from approximately 100 km up to the widths of the oceans themselves are examined. Data include: shape of geoid, quasi-stationary anomalies due to spatial variations in sea density and steady current systems, and the time dependent variations due to tidal and meteorological forces and to varying currents.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yun, Yuxing; Fan, Jiwen; Xiao, Heng
Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32more » km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.« less
Regional Simulations of Stratospheric Lofting of Smoke Plumes
NASA Astrophysics Data System (ADS)
Stenchikov, G. L.; Fromm, M.; Robock, A.
2006-12-01
The lifetime and spatial distribution of sooty aerosols from multiple fires that would cause major climate impact were debated in studies of climatic and environmental consequences of a nuclear war in the 1980s. The Kuwait oil fires in 1991 did not show a cumulative effect of multiple smoke plumes on large-scale circulation systems and smoke was mainly dispersed in the middle troposphere. However, recent observations show that smoke from large forest fires can be directly injected into the lower stratosphere by strong pyro-convective storms. Smoke plumes in the upper troposphere can be partially mixed into the lower stratosphere because of the same heating and lofting effect that was simulated in large-scale nuclear winter simulations with interactive aerosols. However nuclear winter simulations were conducted using climate models with grid spacing of more than 100 km, which do not account for the fine-scale dynamic processes. Therefore in this study we conduct fine-scale regional simulations of the aerosol plume using the Regional Atmospheric Modeling System (RAMS) mesoscale model which was modified to account for radiatively interactive tracers. To resolve fine-scale dynamic processes we use horizontal grid spacing of 25 km and 60 vertical layers, and initiate simulations with the NCEP reanalysis fields. We find that dense aerosol layers could be lofted from 1 to a few km per day, but this critically depends on the optical depth of aerosol layer, single scatter albedo, and how fast the plume is being diluted. Kuwaiti plumes from different small-area fires reached only 5-6 km altitude and were probably diffused and diluted in the lower and middle troposphere. A plume of 100 km spatial scale initially developed in the upper troposphere tends to penetrate into the stratosphere. Short-term cloud resolving simulations of such a plume show that aerosol heating intensifies small-scale motions that tend to mix smoke polluted air into the lower stratosphere. Regional simulations allow us to more accurately estimate the rate of lifting and spreading of aerosol clouds. But they do not reveal any dynamic processes that could prevent heating and lofting of absorbing aerosols.
Implications of the Observed Mesoscale Variations of Clouds for Earth's Radiation Budget
NASA Technical Reports Server (NTRS)
Rossow, William B.; Delo, Carl; Cairns, Brian; Hansen, James E. (Technical Monitor)
2001-01-01
The effect of small-spatial-scale cloud variations on radiative transfer in cloudy atmospheres currently receives a lot of research attention, but the available studies are not very clear about which spatial scales are important and report a very large range of estimates of the magnitude of the effects. Also, there have been no systematic investigations of how to measure and represent these cloud variations. We exploit the cloud climatology produced by the International Satellite Cloud Climatology Project (ISCCP) to: (1) define and test different methods of representing cloud variation statistics, (2) investigate the range of spatial scales that should be included, (3) characterize cloud variations over a range of space and time scales covering mesoscale (30 - 300 km, 3-12 hr) into part of the lower part of the synoptic scale (300 - 3000 km, 1-30 days), (4) obtain a climatology of the optical thickness, emissivity and cloud top temperature variability of clouds that can be used in weather and climate GCMS, together with the parameterization proposed by Cairns et al. (1999), to account for the effects of small-scale cloud variations on radiative fluxes, and (5) evaluate the effect of observed cloud variations on Earth's radiation budget. These results lead to the formulation of a revised conceptual model of clouds for use in radiative transfer calculations in GCMS. The complete variability climatology can be obtained from the ISCCP Web site at http://isccp.giss.nasa.gov.
Starr, James C.; Torgersen, Christian E.
2015-01-01
We compared the assemblage structure, spatial distributions, and habitat associations of mountain whitefish (Prosopium williamsoni) morphotypes and size classes. We hypothesised that morphotypes would have different spatial distributions and would be associated with different habitat features based on feeding behaviour and diet. Spatially continuous sampling was conducted over a broad extent (29 km) in the Calawah River, WA (USA). Whitefish were enumerated via snorkelling in three size classes: small (10–29 cm), medium (30–49 cm), and large (≥50 cm). We identified morphotypes based on head and snout morphology: a pinocchio form that had an elongated snout and a normal form with a blunted snout. Large size classes of both morphotypes were distributed downstream of small and medium size classes, and normal whitefish were distributed downstream of pinocchio whitefish. Ordination of whitefish assemblages with nonmetric multidimensional scaling revealed that normal whitefish size classes were associated with higher gradient and depth, whereas pinocchio whitefish size classes were positively associated with pool area, distance upstream, and depth. Reach-scale generalised additive models indicated that normal whitefish relative density was associated with larger substrate size in downstream reaches (R2 = 0.64), and pinocchio whitefish were associated with greater stream depth in the reaches farther upstream (R2 = 0.87). These results suggest broad-scale spatial segregation (1–10 km), particularly between larger and more phenotypically extreme individuals. These results provide the first perspective on spatial distributions and habitat relationships of polymorphic mountain whitefish.
Classification and its scale analysis of Severe Haze recently observed in Korea
NASA Astrophysics Data System (ADS)
Lee, K. M.; Eun, S. H.; Kim, B. G.; Kim, S. W.; Park, J. S.
2015-12-01
Cloud-aerosol-precipitation interactions mechanism is heavily dependent upon scale problems, and thus the first thing to understand its mechanism is to quantify the time (or spatial) scale of forcing driver, aerosols. This study is focused on recently occurring dense haze episodes accompanied with severe visibility impairment from 2011 to 2013 at two adjacent monitoring stations (Baengnyeongdo and Seoul) in Korea. Baengnyeongdo is an island being located 200 km west from Seoul. First of all, we have tested various flow charts to classify the various categories of heavy haze events by making use of aerosol scattering coefficient, PM2.5, and time lag difference of PM2.5 increase time at both stations, backward trajectories, and the ratio of PM2.5 to PM10 specifically in the quantitative perspective. One of them is selected for this study. Long range transported haze (LH) and Yellow Sand (YS) show very distinctive time lags of both PM2.5 and PM10 between both stations, but much higher ratio of PM2.5 to PM10 for LH in comparison with YS. Meanwhile urban haze (UH) has a significant increase in PM2.5 only at Seoul as easily expected. Time scales (e-folding time) of aerosol light scattering coefficients for LH and UH are 6-12 hrs and 7-16 hrs, respectively calculated for several episodes according to the criteria developed, which eventually corresponds to spatial scale of 120 - 240 km, 140 - 320 km, respectively by assuming average boundary wind speed, 5.6 m/s (Anderson et al., 2003). In general, long-range transported hazes have larger temporal and spatial dimension (about meso-a scale) than domestic hazes, after carefully designed classification of haze episodes. These results can be an useful basis for the estimation of regional aerosol radiative forcings in East Asia.
NASA Astrophysics Data System (ADS)
Tang, U. W.; Wang, Z. S.
2008-10-01
Each city has its unique urban form. The importance of urban form on sustainable development has been recognized in recent years. Traditionally, air quality modelling in a city is in a mesoscale with grid resolution of kilometers, regardless of its urban form. This paper introduces a GIS-based air quality and noise model system developed to study the built environment of highly compact urban forms. Compared with traditional mesoscale air quality model system, the present model system has a higher spatial resolution down to individual buildings along both sides of the street. Applying the developed model system in the Macao Peninsula with highly compact urban forms, the average spatial resolution of input and output data is as high as 174 receptor points per km2. Based on this input/output dataset with a high spatial resolution, this study shows that even the highly compact urban forms can be fragmented into a very small geographic scale of less than 3 km2. This is due to the significant temporal variation of urban development. The variation of urban form in each fragment in turn affects air dispersion, traffic condition, and thus air quality and noise in a measurable scale.
Uranium and Radon in Private Bedrock Well Water in Maine: Geospatial Analysis at Two Scales
2015-01-01
In greater Augusta of central Maine, 53 out of 1093 (4.8%) private bedrock well water samples from 1534 km2 contained [U] >30 μg/L, the U.S. Environmental Protection Agency’s (EPA) Maximum Contaminant Level (MCL) for drinking water; and 226 out of 786 (29%) samples from 1135 km2 showed [Rn] >4,000 pCi/L (148 Bq/L), the U.S. EPA’s Alternative MCL. Groundwater pH, calcite dissolution and redox condition are factors controlling the distribution of groundwater U but not Rn due to their divergent chemical and hydrological properties. Groundwater U is associated with incompatible elements (S, As, Mo, F, and Cs) in water samples within granitic intrusions. Elevated [U] and [Rn] are located within 5–10 km distance of granitic intrusions but do not show correlations with metamorphism at intermediate scales (100−101 km). This spatial association is confirmed by a high-density sampling (n = 331, 5–40 samples per km2) at local scales (≤10–1 km) and the statewide sampling (n = 5857, 1 sample per 16 km2) at regional scales (102–103 km). Wells located within 5 km of granitic intrusions are at risk of containing high levels of [U] and [Rn]. Approximately 48 800–63 900 and 324 000 people in Maine are estimated at risk of exposure to U (>30 μg/L) and Rn (>4000 pCi/L) in well water, respectively. PMID:24655434
Herbivorous fishes, ecosystem function and mobile links on coral reefs
NASA Astrophysics Data System (ADS)
Welsh, J. Q.; Bellwood, D. R.
2014-06-01
Understanding large-scale movement of ecologically important taxa is key to both species and ecosystem management. Those species responsible for maintaining functional connectivity between habitats are often called mobile links and are regarded as essential elements of resilience. By providing connectivity, they support resilience across spatial scales. Most marine organisms, including fishes, have long-term, biogeographic-scale connectivity through larval movement. Although most reef species are highly site attached after larval settlement, some taxa may also be able to provide rapid, reef-scale connectivity as adults. On coral reefs, the identity of such taxa and the extent of their mobility are not yet known. We use acoustic telemetry to monitor the movements of Kyphosus vaigiensis, one of the few reef fishes that feeds on adult brown macroalgae. Unlike other benthic herbivorous fish species, it also exhibits large-scale (>2 km) movements. Individual K. vaigiensis cover, on average, a 2.5 km length of reef (11 km maximum) each day. These large-scale movements suggest that this species may act as a mobile link, providing functional connectivity, should the need arise, and helping to support functional processes across habitats and spatial scales. An analysis of published studies of home ranges in reef fishes found a consistent relationship between home range size and body length. K. vaigiensis is the sole herbivore to depart significantly from the expected home range-body size relationship, with home range sizes more comparable to exceptionally mobile large pelagic predators rather than other reef herbivores. While the large-scale movements of K. vaigiensis reveal its potential capacity to enhance resilience over large areas, it also emphasizes the potential limitations of small marine reserves to protect some herbivore populations.
NASA Astrophysics Data System (ADS)
Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo
2014-05-01
Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have repeated this procedure for soil water content in the 0 to 5 cm and 0 to 10 cm depths. For each case we have compared the variance of filtered soil water content with the expected accuracy of SMAP soil water content. The two areas are very different as regards morphology and soil formation. The Valle Telesina is characterized by a very significant variability of soil hydrological properties leading to complex patterns in soil water content. Contrariwise, the soil properties estimated for all soil mapping units in the Dhoukkala collapse into just two pairs of water retention and hydraulic conductivity characteristics, leading to smoother patterns of soil water content.
Moses, C.S.; Andrefouet, S.; Kranenburg, C.; Muller-Karger, F. E.
2009-01-01
Using imagery at 30 m spatial resolution from the most recent Landsat satellite, the Landsat 7 Enhanced Thematic Mapper Plus (ETM+), we scale up reef metabolic productivity and calcification from local habitat-scale (10 -1 to 100 km2) measurements to regional scales (103 to 104 km2). Distribution and spatial extent of the North Florida Reef Tract (NFRT) habitats come from supervised classification of the Landsat imagery within independent Landsat-derived Millennium Coral Reef Map geomorphologic classes. This system minimizes the depth range and variability of benthic habitat characteristics found in the area of supervised classification and limits misclassification. Classification of Landsat imagery into 5 biotopes (sand, dense live cover, sparse live cover, seagrass, and sparse seagrass) by geomorphologic class is >73% accurate at regional scales. Based on recently published habitat-scale in situ metabolic measurements, gross production (P = 3.01 ?? 109 kg C yr -1), excess production (E = -5.70 ?? 108 kg C yr -1), and calcification (G = -1.68 ?? 106 kg CaCO 3 yr-1) are estimated over 2711 km2 of the NFRT. Simple models suggest sensitivity of these values to ocean acidification, which will increase local dissolution of carbonate sediments. Similar approaches could be applied over large areas with poorly constrained bathymetry or water column properties and minimal metabolic sampling. This tool has potential applications for modeling and monitoring large-scale environmental impacts on reef productivity, such as the influence of ocean acidification on coral reef environments. ?? Inter-Research 2009.
Observations of fine scale structure in the mesosphere and lower thermosphere
NASA Astrophysics Data System (ADS)
Thrane, E. V.; Grandal, B.
1980-06-01
An electrostatic probe designed to measure ion density with high time resolution and accuracy was flown on a Nike-Apache rocket from Andoeya Rocket Range on March 1 1978. Spectra of the spatial density fluctuations were derived in one kilometer height intervals from 65 to 127 km. Below 95 km the power spectra had a slope of about -5/3, as expected for isotropic turbulence. Above 95 km the fluctuations were stronger and showed a white noise power spectrum. These fluctuations are most likely due to plasma instabilities.
NASA Astrophysics Data System (ADS)
Bergström, Per; Lindegarth, Susanne; Lindegarth, Mats
2013-10-01
Human pressures on coastal seas are increasing and methods for sustainable management, including spatial planning and mitigative actions, are therefore needed. In coastal areas worldwide, the development of mussel farming as an economically and ecologically sustainable industry requires geographic information on the growth and potential production capacity. In practice this means that coherent maps of temporally stable spatial patterns of growth need to be available in the planning process and that maps need to be based on mechanistic or empirical models. Therefore, as a first step towards development of models of growth, we assessed empirically the fundamental requirement that there are temporally consistent spatial patterns of growth in the blue mussel, Mytilus edulis. Using a pilot study we designed and dimensioned a transplant experiment, where the spatial consistency in the growth of mussels was evaluated at two resolutions. We found strong temporal and scale-dependent spatial variability in growth but patterns suggested that spatial patterns were uncoupled between growth of shell and that of soft tissue. Spatial patterns of shell growth were complex and largely inconsistent among years. Importantly, however, the growth of soft tissue was qualitatively consistent among years at the scale of km. The results suggest that processes affecting the whole coastal area cause substantial differences in growth of soft tissue among years but that factors varying at the scale of km create strong and persistent spatial patterns of growth, with a potential doubling of productivity by identifying the most suitable locations. We conclude that the observed spatial consistency provides a basis for further development of predictive modelling and mapping of soft tissue growth in these coastal areas. Potential causes of observed patterns, consequences for mussel-farming as a tool for mitigating eutrophication, aspects of precision of modelling and sampling of mussel growth as well as ecological functions in general are discussed.
NASA Astrophysics Data System (ADS)
Lin, S.; Li, J.; Liu, Q.
2018-04-01
Satellite remote sensing data provide spatially continuous and temporally repetitive observations of land surfaces, and they have become increasingly important for monitoring large region of vegetation photosynthetic dynamic. But remote sensing data have their limitation on spatial and temporal scale, for example, higher spatial resolution data as Landsat data have 30-m spatial resolution but 16 days revisit period, while high temporal scale data such as geostationary data have 30-minute imaging period, which has lower spatial resolution (> 1 km). The objective of this study is to investigate whether combining high spatial and temporal resolution remote sensing data can improve the gross primary production (GPP) estimation accuracy in cropland. For this analysis we used three years (from 2010 to 2012) Landsat based NDVI data, MOD13 vegetation index product and Geostationary Operational Environmental Satellite (GOES) geostationary data as input parameters to estimate GPP in a small region cropland of Nebraska, US. Then we validated the remote sensing based GPP with the in-situ measurement carbon flux data. Results showed that: 1) the overall correlation between GOES visible band and in-situ measurement photosynthesis active radiation (PAR) is about 50 % (R2 = 0.52) and the European Center for Medium-Range Weather Forecasts ERA-Interim reanalysis data can explain 64 % of PAR variance (R2 = 0.64); 2) estimating GPP with Landsat 30-m spatial resolution data and ERA daily meteorology data has the highest accuracy(R2 = 0.85, RMSE < 3 gC/m2/day), which has better performance than using MODIS 1-km NDVI/EVI product import; 3) using daily meteorology data as input for GPP estimation in high spatial resolution data would have higher relevance than 8-day and 16-day input. Generally speaking, using the high spatial resolution and high frequency satellite based remote sensing data can improve GPP estimation accuracy in cropland.
NASA Astrophysics Data System (ADS)
Shiga, Yoichi P.; Tadić, Jovan M.; Qiu, Xuemei; Yadav, Vineet; Andrews, Arlyn E.; Berry, Joseph A.; Michalak, Anna M.
2018-01-01
Recent studies have shown the promise of remotely sensed solar-induced chlorophyll fluorescence (SIF) in informing terrestrial carbon exchange, but analyses have been limited to either plot level ( 1 km2) or hemispheric/global ( 108 km2) scales due to the lack of a direct measure of carbon exchange at intermediate scales. Here we use a network of atmospheric CO2 observations over North America to explore the value of SIF for informing net ecosystem exchange (NEE) at regional scales. We find that SIF explains space-time NEE patterns at regional ( 100 km2) scales better than a variety of other vegetation and climate indicators. We further show that incorporating SIF into an atmospheric inversion leads to a spatial redistribution of NEE estimates over North America, with more uptake attributed to agricultural regions and less to needleleaf forests. Our results highlight the synergy of ground-based and spaceborne carbon cycle observations.
Vatland, Shane J.; Gresswell, Robert E.; Poole, Geoffrey C.
2015-01-01
Accurately quantifying stream thermal regimes can be challenging because stream temperatures are often spatially and temporally heterogeneous. In this study, we present a novel modeling framework that combines stream temperature data sets that are continuous in either space or time. Specifically, we merged the fine spatial resolution of thermal infrared (TIR) imagery with hourly data from 10 stationary temperature loggers in a 100 km portion of the Big Hole River, MT, USA. This combination allowed us to estimate summer thermal conditions at a relatively fine spatial resolution (every 100 m of stream length) over a large extent of stream (100 km of stream) during during the warmest part of the summer. Rigorous evaluation, including internal validation, external validation with spatially continuous instream temperature measurements collected from a Langrangian frame of reference, and sensitivity analyses, suggests the model was capable of accurately estimating longitudinal patterns in summer stream temperatures for this system Results revealed considerable spatial and temporal heterogeneity in summer stream temperatures and highlighted the value of assessing thermal regimes at relatively fine spatial and temporal scales. Preserving spatial and temporal variability and structure in abiotic stream data provides a critical foundation for understanding the dynamic, multiscale habitat needs of mobile stream organisms. Similarly, enhanced understanding of spatial and temporal variation in dynamic water quality attributes, including temporal sequence and spatial arrangement, can guide strategic placement of monitoring equipment that will subsequently capture variation in environmental conditions directly pertinent to research and management objectives.
NASA Astrophysics Data System (ADS)
Switzer, A.; Yap, W.; Lauro, F.; Gouramanis, C.; Dominey-Howes, D.; Labbate, M.
2016-12-01
This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.
NASA Astrophysics Data System (ADS)
Sorooshian, S.; Nguyen, P.; Hsu, K. L.
2017-12-01
This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.
Forest amount affects soybean productivity in Brazilian agricultural frontier
NASA Astrophysics Data System (ADS)
Rattis, L.; Brando, P. M.; Marques, E. Q.; Queiroz, N.; Silverio, D. V.; Macedo, M.; Coe, M. T.
2017-12-01
Over the past three decades, large tracts of tropical forests have been converted to crop and pasturelands across southern Amazonia, largely to meet the increasing worldwide demand for protein. As the world's population continue to grow and consume more protein per capita, forest conversion to grow more crops could be a potential solution to meet such demand. However, widespread deforestation is expected to negatively affect crop productivity via multiple pathways (e.g., thermal regulation, rainfall, local moisture, pest control, among others). To quantify how deforestation affects crop productivity, we modeled the relationship between forest amount and enhanced vegetation index (EVI—a proxy for crop productivity) during the soybean planting season across southern Amazonia. Our hypothesis that forest amount causes increased crop productivity received strong support. We found that the maximum MODIS-based EVI in soybean fields increased as a function of forest amount across three spatial-scales, 0.5 km, 1 km, 2 km, 5 km, 10 km, 15 km and 20 km. However, the strength of this relationship varied across years and with precipitation, but only at the local scale (e.g., 500 meters and 1 km radius). Our results highlight the importance of considering forests to design sustainable landscapes.
NASA Astrophysics Data System (ADS)
Pollyea, R.; Mohammadi, N.; Taylor, J. E.
2017-12-01
The annual earthquake rate in Oklahoma increased dramatically between 2009 and 2016, owing in large part to the rapid proliferation of salt water disposal wells associated with unconventional oil and gas recovery. This study presents a geospatial analysis of earthquake occurrence and SWD injection volume within a 68,420 km2 area in north-central Oklahoma between 2011 and 2016. The spatial co-variability of earthquake occurrence and SWD injection volume is analyzed for each year of the study by calculating the geographic centroid for both earthquake epicenter and volume-weighted well location. In addition, the spatial cross correlation between earthquake occurrence and SWD volume is quantified by calculating the cross semivariogram annually for a 9.6 km × 9.6 km (6 mi × 6 mi) grid over the study area. Results from these analyses suggest that the relationship between volume-weighted well centroids and earthquake centroids generally follow pressure diffusion space-time scaling, and the volume-weighted well centroid predicts the geographic earthquake centroid within a 1σ radius of gyration. The cross semivariogram calculations show that SWD injection volume and earthquake occurrence are spatially cross correlated between 2014 and 2016. These results also show that the strength of cross correlation decreased from 2015 to 2016; however, the cross correlation length scale remains unchanged at 125 km. This suggests that earthquake mitigation efforts have been moderately successful in decreasing the strength of cross correlation between SWD volume and earthquake occurrence near-field, but the far-field contribution of SWD injection volume to earthquake occurrence remains unaffected.
The complex jet- and bar-perturbed kinematics in NGC 3393 as revealed with ALMA and GEMINI-GMOS/IFU
NASA Astrophysics Data System (ADS)
Finlez, Carolina; Nagar, Neil M.; Storchi-Bergmann, Thaisa; Schnorr-Müller, Allan; Riffel, Rogemar A.; Lena, Davide; Mundell, C. G.; Elvis, Martin S.
2018-06-01
NGC 3393, a nearby Seyfert 2 galaxy with nuclear radio jets, large-scale and nuclear bars, and a posited secondary super massive black hole, provides an interesting laboratory to test the physics of inflows and outflows. Here we present and analyse the molecular gas (ALMA observations of CO J:2-1 emission over a field of view (FOV) of 45" × 45", at 0."56 (143 pc) spatial and 5 km/s spectral resolution), ionised gas and stars (GEMINI-GMOS/IFU; over a FOV of 4" × 5", at 0."62 (159 pc) spatial and 23 km/s spectral resolution) in NGC 3393. The ionised gas emission, detected over the complete GEMINI-GMOS FOV, has three identifiable kinematic components. A narrow (σ < 115 km/s) component present in the complete FOV, which is consistent with rotation in the galaxy disk. A broad (σ > 115 km/s) redshifted component, detected near the NE and SW radio lobes; which we interpret as a radio jet driven outflow. And a broad (σ > 115 km/s) blueshifted component that shows high velocities in a region perpendicular to the radio jet axis; we interpret this as an equatorial outflow. The CO J:2-1 emission is detected in spiral arms on 5" - 20" scales, and in two disturbed circumnuclear regions. The molecular kinematics in the spiral arms can be explained by rotation. The highly disturbed kinematics of the inner region can be explained by perturbations induced by the nuclear bar and interactions with the large scale bar. We find no evidence for, but cannot strongly rule out, the presence of the posited secondary black hole.
Michez, Adrien; Piégay, Hervé; Lejeune, Philippe; Claessens, Hugues
2017-11-01
Riparian buffers are of major concern for land and water resource managers despite their relatively low spatial coverage. In Europe, this concern has been acknowledged by different environmental directives which recommend multi-scale monitoring (from local to regional scales). Remote sensing methods could be a cost-effective alternative to field-based monitoring, to build replicable "wall-to-wall" monitoring strategies of large river networks and associated riparian buffers. The main goal of our study is to extract and analyze various parameters of the riparian buffers of up to 12,000 km of river in southern Belgium (Wallonia) from three-dimensional (3D) point clouds based on LiDAR and photogrammetric surveys to i) map riparian buffers parameters on different scales, ii) interpret the regional patterns of the riparian buffers and iii) propose new riparian buffer management indicators. We propose different strategies to synthesize and visualize relevant information at different spatial scales ranging from local (<10 km) to regional scale (>12,000 km). Our results showed that the selected parameters had a clear regional pattern. The reaches of Ardenne ecoregion have channels with the highest flow widths and shallowest depths. In contrast, the reaches of the Loam ecoregion have the narrowest and deepest flow channels. Regional variability in channel width and depth is used to locate management units potentially affected by human impact. Riparian forest of the Loam ecoregion is characterized by the lowest longitudinal continuity and mean tree height, underlining significant human disturbance. As the availability of 3D point clouds at the regional scale is constantly growing, our study proposes reproducible methods which can be integrated into regional monitoring by land managers. With LiDAR still being relatively expensive to acquire, the use of photogrammetric point clouds combined with LiDAR data is a cost-effective means to update the characterization of the riparian forest conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.
Pearse, Aaron T.; Kaminski, Richard M.; Reinecke, Kenneth J.; Dinsmore, Stephen J.
2012-01-01
Landscape features influence distribution of waterbirds throughout their annual cycle. A conceptual model, the wetland habitat complex, may be useful in conservation of wetland habitats for dabbling ducks (Anatini). The foundation of this conceptual model is that ducks seek complexes of wetlands containing diverse resources to meet dynamic physiological needs. We included flooded croplands, wetlands and ponds, public-land waterfowl sanctuary, and diversity of habitats as key components of wetland habitat complexes and compared their relative influence at two spatial scales (i.e., local, 0.25-km radius; landscape, 4-km) on dabbling ducks wintering in western Mississippi, USA during winters 2002–2004. Distribution of mallard (Anas platyrhynchos) groups was positively associated with flooded cropland at local and landscape scales. Models representing flooded croplands at the landscape scale best explained occurrence of other dabbling ducks. Habitat complexity measured at both scales best explained group size of other dabbling ducks. Flooded croplands likely provided food that had decreased in availability due to conversion of wetlands to agriculture. Wetland complexes at landscape scales were more attractive to wintering ducks than single or structurally simple wetlands. Conservation of wetland complexes at large spatial scales (≥5,000 ha) on public and private lands will require coordination among multiple stakeholders.
Spatial dynamics of deforestation and forest fragmentation (1930-2013) in Eastern Ghats, India
NASA Astrophysics Data System (ADS)
Sudhakar Reddy, C.; Jha, C. S.; Dadhwal, V. K.
2014-11-01
The tropical forests are the most unique ecosystems for their potential economic value. Eastern Ghats, a phytogeographical region of India has rugged hilly terrain distributed in parts of five states, viz. Odisha, Andhra Pradesh, Telangana, Karnataka and Tamil Nadu. The present study is mainly aimed to analyse the trends in deforestation and its role in forest fragmentation of Eastern Ghats. The long term changes in forest cover with its spatial pattern over time has been assessed by analyzing a set of topographical maps and satellite remote sensing datasets. The multi-source and multi-date mapping has been carried out using survey of India topographical maps (1930's), Landsat MSS (1975 and 1985), IRS 1B LISS-I (1995), IRS P6 AWiFS (2005) and Resourcesat-2 AWiFS (2013) satellite images. The classified spatial data for 1930, 1975, 1985, 1995, 2005 and 2013 showed that the forest cover for the mentioned years are 102213 km2 (45.6 %), 76630 (34.2 %), 73416 km2 (32.7 %), 71730 km2 (32 %), 71305 km2 (31.8 %) and 71186 km2 (31.7 %) of the geographical area of Eastern Ghats respectively. A spatial statistical analysis of the deforestation rates and forest cover change were carried out based on distinctive time phases, i.e. 1930-1975, 1975-1985, 1985-1995, 1995-2005 and 2005-2013. The spatial analysis was carried out first by segmenting the study area into grid cells of 5 km x 5 km for time series assessment and determining spatial changes in forests. The distribution of loss and gain of forest was calculated across six classes i.e. <1 km2, 1-5 km2, 5-10 km2, 10-15 km2, 15-20 km2 and >20 km2. Landscape metrics were used to quantify spatial variability of landscape structure and composition. The results of study on net rate of deforestation was found to be 0.64 during 1935 to 1975, 0.43 during 1975-1985, 0.23 during 1985-1995, 0.06 during 1995-2005 and 0.02 during 2005-2013. The number of forest patches increased from 2688 (1930) to 13009 (2013). The largest forest patch in 1930 represents area of 41669 km2 that has reduced to 27800 km2 by 2013. Thus, it is evident that there is a substantial reduction in the size of the very large forest patches due to deforestation. According to spatial analysis, among the different land use change drivers, agriculture occupies highest area, followed by degradation to scrub and conversion to orchards. The dominant forest type was dry deciduous which comprises 37192 km2 (52.2 %) of the total forest area of Eastern Ghats, followed by moist deciduous forest (39.2 %) and semievergreen forest (4.8 %) in 2013. The change analysis showed that the large scale negative changes occurred in deciduous forests and semi-evergreen forests compared to wet evergreen forests due to high economic potential and accessibility. This study has quantified the deforestation that has taken place over the last eight decades in the Eastern Ghats. The decline in overall rate of deforestation in recent years indicates increased measures of conservation. The change analysis of deforestation and forest fragmentation provides a decisive component for conservation and helpful in long term management of forests of Eastern Ghats.
Rapid divergence of mussel populations despite incomplete barriers to dispersal.
Maas, Diede L; Prost, Stefan; Bi, Ke; Smith, Lydia L; Armstrong, Ellie E; Aji, Ludi P; Toha, Abdul Hamid A; Gillespie, Rosemary G; Becking, Leontine E
2018-04-01
Striking genetic structure among marine populations at small spatial scales is becoming evident with extensive molecular studies. Such observations suggest isolation at small scales may play an important role in forming patterns of genetic diversity within species. Isolation-by-distance, isolation-by-environment and historical priority effects are umbrella terms for a suite of processes that underlie genetic structure, but their relative importance at different spatial and temporal scales remains elusive. Here, we use marine lakes in Indonesia to assess genetic structure and assess the relative roles of the processes in shaping genetic differentiation in populations of a bivalve mussel (Brachidontes sp.). Marine lakes are landlocked waterbodies of similar age (6,000-10,000 years), but with heterogeneous environments and varying degrees of connection to the sea. Using a population genomic approach (double-digest restriction-site-associated DNA sequencing), we show strong genetic structuring across populations (range F ST : 0.07-0.24) and find limited gene flow through admixture plots. At large spatial scales (>1,400 km), a clear isolation-by-distance pattern was detected. At smaller spatial scales (<200 km), this pattern is maintained, but accompanied by an association of genetic divergence with degree of connection. We hypothesize that (incomplete) dispersal barriers can cause initial isolation, allowing priority effects to give the numerical advantage necessary to initiate strong genetic structure. Priority effects may be strengthened by local adaptation, which the data may corroborate by showing a high correlation between mussel genotypes and temperature. Our study indicates an often-neglected role of (evolution-mediated) priority effects in shaping population divergence. © 2018 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.
Preliminary simulations of the large-scale environment during the FIRE cirrus IFO
NASA Technical Reports Server (NTRS)
Westphal, Douglas L.; Toon, Owen B.
1990-01-01
Large scale forcing (scales greater than 500 km) is the dominant factor in the generation, maintenance, and dissipation of cirrus cloud systems. However, the analyses of data acquired during the first Cirrus IFO have highlighted the importance of mesoscale processes (scales of 20 to 500 km) to the development of cirrus cloud systems. Unfortunately, Starr and Wylie found that the temporal and spatial resolution of the standard and supplemental rawinsonde data were insufficient to allow an explanation of all of the mesoscale cloud features that were present on the 27 to 28 Oct. 1986. It is described how dynamic initialization, or 4-D data assimilation (FDDA) can provide a method to address this problem. The first steps towards application of FDDA to FIRE are also described.
NASA Astrophysics Data System (ADS)
Martin, D. J.
2013-12-01
Large woody debris (LWD) is universally recognized as a key component of the geomorphological and ecological function of fluvial systems and has been increasingly incorporated into stream restoration and watershed management projects. However, 'natural' processes of recruitment and the subsequent arrangement of LWD within the river network are poorly understood and are thus, rarely a management consideration. Additionally, LWD research tends to be regionally biased toward mountainous regions, and scale biased toward the micro-scale. In many locations, the lack of understanding has led to the failure of restoration/rehabilitation projects that involved the use of LWD. This research uses geographic information systems and spatial analysis techniques to investigate longitudinal arrangement patterns of LWD in a low-gradient, Midwestern river. A large-scale GPS inventory of LWD was performed on the Big River, located in the eastern Missouri Ozarks resulting in over 5,000 logged positions of LWD along seven river segments covering nearly 100 km of the 237 km river system. A time series analysis framework was used to statistically identify longitudinal spatial patterns of LWD arrangement along the main stem of the river, and correlation analyses were performed to help identify physical controls of those patterns. Results indicate that upstream segments have slightly lower densities than downstream segments, with the exception of the farthest upstream segment. Results also show lack of an overall longitudinal trend in LWD density; however, periodogram analysis revealed an inherent periodicity in LWD arrangement. Periodicities were most evident in the downstream segments with frequencies ranging from 3 km to 7 km. Additionally, Pearson correlation analysis, performed within the segment displaying the strongest periodic behavior, show that LWD densities are correlated with channel sinuosity (r=0.25). Ongoing research is investigating further relationships between arrangement patterns and geomorphic and riparian variables. Understanding these spatial patterns and relationships will provide valuable insight into the application of LWD-related stream and watershed management practices, and fill a necessary regional knowledge gap in our understanding of LWD's role in fluvial processes.
NASA Astrophysics Data System (ADS)
Bindhu, V. M.; Narasimhan, B.
2015-03-01
Normalized Difference Vegetation Index (NDVI), a key parameter in understanding the vegetation dynamics, has high spatial and temporal variability. However, continuous monitoring of NDVI is not feasible at fine spatial resolution (<60 m) owing to the long revisit time needed by the satellites to acquire the fine spatial resolution data. Further, the study attains significance in the case of humid tropical regions of the earth, where the prevailing atmospheric conditions restrict availability of fine resolution cloud free images at a high temporal frequency. As an alternative to the lack of high resolution images, the current study demonstrates a novel disaggregation method (DisNDVI) which integrates the spatial information from a single fine resolution image and temporal information in terms of crop phenology from time series of coarse resolution images to generate estimates of NDVI at fine spatial and temporal resolution. The phenological variation of the pixels captured at the coarser scale provides the basis for relating the temporal variability of the pixel with the NDVI available at fine resolution. The proposed methodology was tested over a 30 km × 25 km spatially heterogeneous study area located in the south of Tamil Nadu, India. The robustness of the algorithm was assessed by an independent comparison of the disaggregated NDVI and observed NDVI obtained from concurrent Landsat ETM+ imagery. The results showed good spatial agreement across the study area dominated with agriculture and forest pixels, with a root mean square error of 0.05. The validation done at the coarser scale showed that disaggregated NDVI spatially averaged to 240 m compared well with concurrent MODIS NDVI at 240 m (R2 > 0.8). The validation results demonstrate the effectiveness of DisNDVI in improving the spatial and temporal resolution of NDVI images for utility in fine scale hydrological applications such as crop growth monitoring and estimation of evapotranspiration.
Cornell, K.L.; Donovan, T.M.
2010-01-01
Understanding how spatial habitat patterns influence abundance and dynamics of animal populations is a primary goal in landscape ecology. We used an information-theoretic approach to investigate the association between habitat patterns at multiple spatial scales and demographic patterns for black-throated blue warblers (Dendroica caerulescens) at 20 study sites in west-central Vermont, USA from 2002 to 2005. Sites were characterized by: (1) territory-scale shrub density, (2) patch-scale shrub density occurring within 25 ha of territories, and (3) landscape-scale habitat patterns occurring within 5 km radius extents of territories. We considered multiple population parameters including abundance, age ratios, and annual fecundity. Territory-scale shrub density was most important for determining abundance and age ratios, but landscape-scale habitat structure strongly influenced reproductive output. Sites with higher territory-scale shrub density had higher abundance, and were more likely to be occupied by older, more experienced individuals compared to sites with lower shrub density. However, annual fecundity was higher on sites located in contiguously forested landscapes where shrub density was lower than the fragmented sites. Further, effects of habitat pattern at one spatial scale depended on habitat conditions at different scales. For example, abundance increased with increasing territory-scale shrub density, but this effect was much stronger in fragmented landscapes than in contiguously forested landscapes. These results suggest that habitat pattern at different spatial scales affect demographic parameters in different ways, and that effects of habitat patterns at one spatial scale depends on habitat conditions at other scales. ?? Springer Science+Business Media B.V. 2009.
Generation of High Resolution Land Surface Parameters in the Community Land Model
NASA Astrophysics Data System (ADS)
Ke, Y.; Coleman, A. M.; Wigmosta, M. S.; Leung, L.; Huang, M.; Li, H.
2010-12-01
The Community Land Model (CLM) is the land surface model used for the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). It examines the physical, chemical, and biological processes across a variety of spatial and temporal scales. Currently, efforts are being made to improve the spatial resolution of the CLM, in part, to represent finer scale hydrologic characteristics. Current land surface parameters of CLM4.0, in particular plant functional types (PFT) and leaf area index (LAI), are generated from MODIS and calculated at a 0.05 degree resolution. These MODIS-derived land surface parameters have also been aggregated to coarser resolutions (e.g., 0.5, 1.0 degrees). To evaluate the response of CLM across various spatial scales, higher spatial resolution land surface parameters need to be generated. In this study we examine the use of Landsat TM/ETM+ imagery and data fusion techniques for generating land surface parameters at a 1km resolution within the Pacific Northwest United States. . Land cover types and PFTs are classified based on Landsat multi-season spectral information, DEM, National Land Cover Database (NLCD) and the USDA-NASS Crop Data Layer (CDL). For each PFT, relationships between MOD15A2 high quality LAI values, Landsat-based vegetation indices, climate variables, terrain, and laser-altimeter derived vegetation height are used to generate monthly LAI values at a 30m resolution. The high-resolution PFT and LAI data are aggregated to create a 1km model grid resolution. An evaluation and comparison of CLM land surface response at both fine and moderate scale is presented.
Scale-dependent variation in forest structures in naturally dynamic boreal forest landscapes
NASA Astrophysics Data System (ADS)
Kulha, Niko; Pasanen, Leena; De Grandpré, Louis; Kuuluvainen, Timo; Aakala, Tuomas
2017-04-01
Natural forest structures vary at multiple spatial scales. This variation reflects the occurrence of driving factors, such as disturbances and variation in soil or topography. To explore and understand the linkages of forest structural characteristics and factors driving their variation, we need to recognize how the structural characteristics vary in relation to spatial scale. This can be achieved by identifying scale-dependent features in forest structure within unmanaged forest landscapes. By identifying these features and examining their relationship with potential driving factors, we can better understand the dynamics of forest structural development. Here, we examine the spatial variation in forest structures at multiple spatial scales, utilizing data from old-growth boreal forests in two regions with contrasting disturbance regimes: northern Finland and north-eastern Québec, Canada ( 67° 45'N, 29° 36'E, 49° 39'N, 67° 55'W, respectively). The three landscapes (4 km2 each) in Finland are dominated by Pinus sylvestris and Picea abies, whereas the two landscapes in Québec are dominated by Abies balsamea and Picea mariana. Québec's forests are a subject to cyclic outbreaks of the eastern spruce budworm, causing extensive mortality especially in A. balsamea-dominated stands. In the Finnish landscapes, gap- to patch-scale disturbances due to tree senescence, fungi and wind, as well as infrequent surface fires in areas dominated by P. sylvestris, prevail. Owing to the differences in the species compositions and the disturbance regimes, we expect differing scales of variation between the landscapes. To quantify patterns of variation, we visually interpret stereopairs of recent aerial photographs. From the photographs, we collect information on forest canopy coverage, species composition and dead wood. For the interpretation, each 4 km2 plot is divided into 0.1ha square cells (4096 per plot). Interpretations are validated against field observations and compiled to raster maps. We analyze the raster maps with Bayesian scale space approach (iBSiZer), which aims in capturing credible variations at different spatial scales. As a result, we can detect structural entities (e.g. patches with higher canopy cover), which deviate credibly from their surroundings. The detected entities can further be linked to specific drivers. Our results show that the role of a particular driving factor varies in relation to spatial scale. For example, in the Finnish landscapes, topoedaphic factors exerted a stronger control on broad-scale forest structural characteristics, whereas recent disturbances (quantified as the amount of dead wood) appeared to play an important role in explaining the smaller scale variation of forest structures. Here, we showcase the methodology used in the detection of scale-dependent forest structural entities and present the results of our analysis of the spatial scales of variation in the natural boreal forest structures.
NASA Astrophysics Data System (ADS)
Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.
2017-12-01
Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.
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.
NASA Astrophysics Data System (ADS)
Tunaley, C.; Tetzlaff, D.; Lessels, J. S.; Soulsby, C.
2014-12-01
In order to understand aquatic ecosystem functioning it is critical to understand the processes that control the spatial and temporal variations in DOC. DOC concentrations are highly dynamic, however, our understanding at short, high frequency timescales is still limited. Optical sensors which act as a proxy for DOC provide the opportunity to investigate near-continuous DOC variations in order to understand the hydrological and biogeochemical processes that control concentrations at short temporal scales. Here we present inferred 15 minute stream water DOC data for a 12 month period at three nested scales (1km2, 3km2 and 31km2) for the Bruntland Burn, a headwater catchment in NE Scotland. High frequency data were measured using FDOM and CDOM probes which work by measuring the fluorescent component and coloured component, respectively, of DOC when exposed to ultraviolet light. Both FDOM and CDOM were strongly correlated (r2 >0.8) with DOC allowing high frequency estimations. Results show the close coupling of DOC with discharge throughout the sampling period at all three spatial scales. However, analysis at the event scale highlights anticlockwise hysteresis relationships between DOC and discharge due to the delay in DOC being flushed from the increasingly large areas of peaty soils as saturation zones expand and increase hydrological connectivity. Lag times vary between events dependent on antecedent conditions. During a 10 year drought period in late summer 2013 it was apparent that very small changes in discharge on a 15 minute timescale result in high increases in DOC. This suggests transport limitation during this period where DOC builds up in the soil and is not flushed regularly, therefore any subsequent increase in discharge results in large DOC peaks. The high frequency sensors also reveal diurnal variability during summer months related to the photo-oxidation, evaporative and biological influences of DOC during the day. This relationship is less significant during the winter months.
NASA Astrophysics Data System (ADS)
Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René
2017-11-01
Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.
NASA Astrophysics Data System (ADS)
Hendrickx, J. M. H.; Allen, R. G.; Myint, S. W.; Ogden, F. L.
2015-12-01
Large scale mapping of evapotranspiration and root zone soil moisture is only possible when satellite images are used. The spatial resolution of this imagery typically depends on its temporal resolution or the satellite overpass time. For example, the Landsat satellite acquires images at 30 m resolution every 16 days while the MODIS satellite acquires images at 250 m resolution every day. In this study we deal with optical/thermal imagery that is impacted by cloudiness contrary to radar imagery that penetrates through clouds. Due to cloudiness, the temporal resolution of Landsat drops from 16 days to about one clear sky Landsat image per month in the southwestern USA and about one every ten years in the humid tropics of Panama. Only by launching additional satellites can the temporal resolution be improved. Since this is too costly, an alternative is found by using ground measurements with high temporal resolution (from minutes to days) but poor spatial resolution. The challenge for large-scale evapotranspiration and root zone soil moisture mapping is to construct a layer stack consisting of N time layers covering the period of interest each containing M pixels covering the region of interest. We will present examples of the Phoenix Active Management Area in AZ (14,600 km2), Green River Basin in WY (44,000 km2), the Kishwaukee Watershed in IL (3,150 km2), the area covered by Landsat Path 28/Row 35 in OK (30,000 km2) and the Agua Salud Watershed in Panama (200 km2). In these regions we used Landsat or MODIS imagery for mapping evapotranspiration and root zone soil moisture by the algorithm Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) together with meteorological measurements and sometimes either Large Aperture Scintillometers (LAS) or Eddy Covariance (EC). We conclude with lessons learned for future large-scale hydrological studies.
Wang, Chao; Gao, Qiong; Wang, Xian; Yu, Mei
2016-11-22
Uncovering magnitude, trend, and spatial pattern of land cover/land use changes (LCLUC) is crucial for understanding mechanisms of LCLUC and assisting land use planning and conservation. China has been undergoing unprecedented economic growth, massive rural-to-urban migration, and large-scale policy-driven ecological restoration, and therefore encountering enormous LCLUC in recent decades. However, comprehensive understandings of spatiotemporal LCLUC dynamics and underlying mechanisms are still lacking. Based on classification of annual LCLU maps from MODIS satellite imagery, we proposed a land change detection method to capture significant land change hotspots over Northern China during 2001-2013, and further analyzed temporal trends and spatial patterns of LCLUC. We found rapid decline of agricultural land near urban was predominantly caused by urban expansion. The process was especially strong in North China Plain with 14,057 km 2 of urban gain and -21,017 km 2 of agricultural land loss. To offset the loss of agricultural land, Northeast China Plain and Xinjiang were reclaimed. Substantial recovery of forests (49,908 km 2 ) and closed shrubland (60,854 km 2 ) occurred in mountainous regions due to abandoned infertile farmland, secondary succession, and governmental conservation policies. The spatial patterns and trends of LCLUC in Northern China provide information to support effective environmental policies towards sustainable development.
Wang, Chao; Gao, Qiong; Wang, Xian; Yu, Mei
2016-01-01
Uncovering magnitude, trend, and spatial pattern of land cover/land use changes (LCLUC) is crucial for understanding mechanisms of LCLUC and assisting land use planning and conservation. China has been undergoing unprecedented economic growth, massive rural-to-urban migration, and large-scale policy-driven ecological restoration, and therefore encountering enormous LCLUC in recent decades. However, comprehensive understandings of spatiotemporal LCLUC dynamics and underlying mechanisms are still lacking. Based on classification of annual LCLU maps from MODIS satellite imagery, we proposed a land change detection method to capture significant land change hotspots over Northern China during 2001–2013, and further analyzed temporal trends and spatial patterns of LCLUC. We found rapid decline of agricultural land near urban was predominantly caused by urban expansion. The process was especially strong in North China Plain with 14,057 km2 of urban gain and −21,017 km2 of agricultural land loss. To offset the loss of agricultural land, Northeast China Plain and Xinjiang were reclaimed. Substantial recovery of forests (49,908 km2) and closed shrubland (60,854 km2) occurred in mountainous regions due to abandoned infertile farmland, secondary succession, and governmental conservation policies. The spatial patterns and trends of LCLUC in Northern China provide information to support effective environmental policies towards sustainable development. PMID:27874092
NASA Astrophysics Data System (ADS)
Wang, Chao; Gao, Qiong; Wang, Xian; Yu, Mei
2016-11-01
Uncovering magnitude, trend, and spatial pattern of land cover/land use changes (LCLUC) is crucial for understanding mechanisms of LCLUC and assisting land use planning and conservation. China has been undergoing unprecedented economic growth, massive rural-to-urban migration, and large-scale policy-driven ecological restoration, and therefore encountering enormous LCLUC in recent decades. However, comprehensive understandings of spatiotemporal LCLUC dynamics and underlying mechanisms are still lacking. Based on classification of annual LCLU maps from MODIS satellite imagery, we proposed a land change detection method to capture significant land change hotspots over Northern China during 2001-2013, and further analyzed temporal trends and spatial patterns of LCLUC. We found rapid decline of agricultural land near urban was predominantly caused by urban expansion. The process was especially strong in North China Plain with 14,057 km2 of urban gain and -21,017 km2 of agricultural land loss. To offset the loss of agricultural land, Northeast China Plain and Xinjiang were reclaimed. Substantial recovery of forests (49,908 km2) and closed shrubland (60,854 km2) occurred in mountainous regions due to abandoned infertile farmland, secondary succession, and governmental conservation policies. The spatial patterns and trends of LCLUC in Northern China provide information to support effective environmental policies towards sustainable development.
NASA Astrophysics Data System (ADS)
Nijssen, Bart; Clark, Martyn; Mizukami, Naoki; Chegwidden, Oriana
2016-04-01
Most existing hydrological models use a fixed representation of landscape structure. For example, high-resolution, spatially-distributed models may use grid cells that exchange moisture through the saturated subsurface or may divide the landscape into hydrologic response units that only exchange moisture through surface channels. Alternatively, many regional models represent the landscape through coarse elements that do not model any moisture exchange between these model elements. These spatial organizations are often represented at a low-level in the model code and its data structures, which makes it difficult to evaluate different landscape representations using the same hydrological model. Instead, such experimentation requires the use of multiple, different hydrological models, which in turn complicates the analysis, because differences in model outcomes are no longer constrained by differing spatial representations. This inflexibility in the representation of landscape structure also limits a model's capability for scaling local processes to regional outcomes. In this study, we used the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to evaluate different model spatial configurations to represent landscape structure and to evaluate scaling behavior. SUMMA can represent the moisture exchange between arbitrarily shaped landscape elements in a number of different ways, while using the same model parameterizations for vertical fluxes. This allows us to isolate the effects of changes in landscape representations on modeled hydrological fluxes and states. We examine the effects of spatial configuration in Reynolds Creek, Idaho, USA, which is a research watershed with gaged areas from 1-20 km2. We then use the same modeling system to evaluate scaling behavior in simulated hydrological fluxes in the Columbia River Basin, Pacific Northwest, USA. This basin drains more than 500,000 km2 and includes the Reynolds Creek Watershed.
NASA Astrophysics Data System (ADS)
López-Vicente, Manuel, , Dr.; Palazón, M. Sc. Leticia; Quijano, M. Sc. Laura; Gaspar, Leticia, , Dr.; Navas, Ana, , Dr.
2015-04-01
Hydrological and soil erosion models allow mapping and quantifying spatially distributed rates of runoff depth and soil redistribution for different land uses, management and tillage practices and climatic scenarios. The different temporal and spatial [very small (< 1 km2), small (1-5 km2), medium (5-50 km2) and large catchments (50-1000 km2) or river basins (>1000 km2)] scales of numerical simulations make model selection specific to each range of scales. Additionally, the spatial resolution of the inputs is in agreement with the size of the study area. In this study, we run the GIS-based water balance DR2-2013© SAGA v1.1 model (freely downloaded as executable file at http://digital.csic.es/handle/10261/93543), in the Vandunchil stream catchment (23 km2; Ebro river basin, NE Spain). All input maps are generated at 5 x 5 m of cell size (924,573 pixels per map) allowing sound parameterization. Simulation is run at monthly scale with average climatic values. This catchment is an open hydrological system and it has a long history of human occupation, agricultural practices and water management. Numerous manmade infrastructures or landscape linear elements (LLEs: paved and unpaved trails, rock mounds in non-cultivated areas, disperse and small settlements, shallow and long drainage ditches, stone walls, small rock dams, fences and vegetation strips) appear throughout the hillslopes and streams and modify the natural runoff pathways and thus the hydrological and sediment connectivity. Rain-fed cereal fields occupy one third of the catchment area, 1% corresponds to sealed soils, and the remaining area is covered with Mediterranean forest, scrubland, pine afforestation and meadow. The parent material corresponds to Miocene sandstones and lutites and Holocene colluvial and alluvial deposits. The climate is continental Mediterranean with two humid periods, one in spring and a second in autumn that summarizes 63% of the total annual precipitation. We created a synthetic weather station (WS) from the Caseda and Uncastillo WS. The effective rainfall that reaches the soils (after canopy interception and slope correction) was 85% on average from the total rainfall depth (556 mm yr-1) and the average initial runoff, before overland flow processes, was 320 mm yr-1. The simulated effective runoff (CQeff) ranged from 0 until 29,960 mm yr-1 and the corresponding map showed the typical spatial pattern of overland flow pathways though numerous disruptions appeared along the hillslopes and the main streams due to the presence of LLEs. The total depth of annual runoff corresponds to 37.8% of the total effective rainfall (TER) and 32.0% of the total rainfall depth (TR). The remaining volume of water, the soil water content (Waa) associated with the runoff and rainfall events, meant 62.2% and 52.7% of the TER and TR, respectively. The map of the Waa presented a different spatial pattern where the land uses play a more important role than the processes of cumulative overland flow. Significant variations in the monthly values of CQeff and Waa were described. This study proves the ability of the DR2-2013© SAGA v1.1 model to simulate the hydrological response of the soils at catchment scale.
Crustal evolution inferred from Apollo magnetic measurements
NASA Technical Reports Server (NTRS)
Dyal, P.; Daily, W. D.; Vanian, L. L.
1978-01-01
The topology of lunar remanent fields is investigated by analyzing simultaneous magnetometer and solar wind spectrometer data. The diffusion model proposed by Vanyan (1977) to describe the field-plasma interaction at the lunar surface is extended to describe the interaction with fields characterized by two scale lengths, and the extended model is compared with data from three Apollo landing sites (Apollo 12, 15 and 16) with crustal fields of differing intensity and topology. Local remanent field properties from this analysis are compared with high spatial resolution magnetic maps obtained from the electron reflection experiment. It is concluded that remanent fields over most of the lunar surface are characterized by spatial variations as small as a few kilometers. Large regions (50 to 100 km) of the lunar crust were probably uniformly magnetized early in the evolution of the crust. Smaller scale (5 to 10 km) magnetic sources close to the surface were left by bombardment and subsequent gardening of the upper layers of these magnetized regions. The small scale sized remanent fields of about 100 gammas are measured by surface experiments, whereas the larger scale sized fields of about 0.1 gammas are measured by the orbiting subsatellite experiments.
The spatial scale for cisco recruitment dynamics in Lake Superior during 1978-2007
Rook, Benjamin J.; Hansen, Michael J.; Gorman, Owen T.
2012-01-01
The cisco Coregonus artedi was once the most abundant fish species in the Great Lakes, but currently cisco populations are greatly reduced and management agencies are attempting to restore the species throughout the basin. To increase understanding of the spatial scale at which density‐independent and density‐dependent factors influence cisco recruitment dynamics in the Great Lakes, we used a Ricker stock–recruitment model to identify and quantify the appropriate spatial scale for modeling age‐1 cisco recruitment dynamics in Lake Superior. We found that the recruitment variation of ciscoes in Lake Superior was best described by a five‐parameter regional model with separate stock–recruitment relationships for the western, southern, eastern, and northern regions. The spatial scale for modeling was about 260 km (range = 230–290 km). We also found that the density‐independent recruitment rate and the rate of compensatory density dependence varied among regions at different rates. The density‐independent recruitment rate was constant among regions (3.6 age‐1 recruits/spawner), whereas the rate of compensatory density dependence varied 16‐fold among regions (range = −0.2 to −2.9/spawner). Finally, we found that peak recruitment and the spawning stock size that produced peak recruitment varied among regions. Both peak recruitment (0.5–7.1 age‐1 recruits/ha) and the spawning stock size that produced peak recruitment (0.3–5.3 spawners/ha) varied 16‐fold among regions. Our findings support the hypothesis that the factors driving cisco recruitment operate within four different regions of Lake Superior, suggest that large‐scale abiotic factors are more important than small‐scale biotic factors in influencing cisco recruitment, and suggest that fishery managers throughout Lake Superior and the entire Great Lakes basin should address cisco restoration and management efforts on a regional scale in each lake.
Internal variability of a dynamically downscaled climate over North America
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Jiali; Bessac, Julie; Kotamarthi, Rao
This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 km and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemblemore » during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.« less
NASA Astrophysics Data System (ADS)
Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji
2016-10-01
We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.
Habitat predictors of genetic diversity for two sympatric wetland-breeding amphibian species.
McKee, Anna M; Maerz, John C; Smith, Lora L; Glenn, Travis C
2017-08-01
Population genetic diversity is widely accepted as important to the conservation and management of wildlife. However, habitat features may differentially affect evolutionary processes that facilitate population genetic diversity among sympatric species. We measured genetic diversity for two pond-breeding amphibian species (Dwarf salamanders, Eurycea quadridigitata ; and Southern Leopard frogs, Lithobates sphenocephalus ) to understand how habitat characteristics and spatial scale affect genetic diversity across a landscape. Samples were collected from wetlands on a longleaf pine reserve in Georgia. We genotyped microsatellite loci for both species to assess population structures and determine which habitat features were most closely associated with observed heterozygosity and rarefied allelic richness. Both species exhibited significant population genetic structure; however, structure in Southern Leopard frogs was driven primarily by one outlier site. Dwarf salamander allelic richness was greater at sites with less surrounding road area within 0.5 km and more wetland area within 1.0 and 2.5 km, and heterozygosity was greater at sites with more wetland area within 0.5 km. In contrast, neither measure of Southern Leopard frog genetic diversity was associated with any habitat features at any scale we evaluated. Genetic diversity in the Dwarf salamander was strongly associated with land cover variables up to 2.5 km away from breeding wetlands, and/or results suggest that minimizing roads in wetland buffers may be beneficial to the maintenance of population genetic diversity. This study suggests that patterns of genetic differentiation and genetic diversity have associations with different habitat features across different spatial scales for two syntopic pond-breeding amphibian species.
A network model framework for prioritizing wetland conservation in the Great Plains
Albanese, Gene; Haukos, David A.
2017-01-01
ContextPlaya wetlands are the primary habitat for numerous wetland-dependent species in the Southern Great Plains of North America. Plant and wildlife populations that inhabit these wetlands are reciprocally linked through the dispersal of individuals, propagules and ultimately genes among local populations.ObjectiveTo develop and implement a framework using network models for conceptualizing, representing and analyzing potential biological flows among 48,981 spatially discrete playa wetlands in the Southern Great Plains.MethodsWe examined changes in connectivity patterns and assessed the relative importance of wetlands to maintaining these patterns by targeting wetlands for removal based on network centrality metrics weighted by estimates of habitat quality and probability of inundation.ResultsWe identified several distinct, broad-scale sub networks and phase transitions among playa wetlands in the Southern Plains. In particular, for organisms that can disperse >2 km a dense and expansive wetland sub network emerges in the Southern High Plains. This network was characterized by localized, densely connected wetland clusters at link distances (h) >2 km but <5 km and was most sensitive to changes in wetland availability (p) and configuration when h = 4 km, and p = 0.2–0.4. It transitioned to a single, large connected wetland system at broader spatial scales even when the proportion of inundated wetland was relatively low (p = 0.2).ConclusionsOur findings suggest that redundancy in the potential for broad and fine-scale movements insulates this system from damage and facilitates system-wide connectivity among populations with different dispersal capacities.
Large scale, synchronous variability of marine fish populations driven by commercial exploitation.
Frank, Kenneth T; Petrie, Brian; Leggett, William C; Boyce, Daniel G
2016-07-19
Synchronous variations in the abundance of geographically distinct marine fish populations are known to occur across spatial scales on the order of 1,000 km and greater. The prevailing assumption is that this large-scale coherent variability is a response to coupled atmosphere-ocean dynamics, commonly represented by climate indexes, such as the Atlantic Multidecadal Oscillation and North Atlantic Oscillation. On the other hand, it has been suggested that exploitation might contribute to this coherent variability. This possibility has been generally ignored or dismissed on the grounds that exploitation is unlikely to operate synchronously at such large spatial scales. Our analysis of adult fishing mortality and spawning stock biomass of 22 North Atlantic cod (Gadus morhua) stocks revealed that both the temporal and spatial scales in fishing mortality and spawning stock biomass were equivalent to those of the climate drivers. From these results, we conclude that greater consideration must be given to the potential of exploitation as a driving force behind broad, coherent variability of heavily exploited fish species.
NASA Astrophysics Data System (ADS)
Torres, A. D.; Keppel-Aleks, G.; Doney, S. C.; Feng, S.; Lauvaux, T.; Fendrock, M. A.; Rheuben, J.
2017-12-01
Remote sensing instruments provide an unprecedented density of observations of the atmospheric CO2 column average mole fraction (denoted as XCO2), which can be used to constrain regional scale carbon fluxes. Inferring fluxes from XCO2 observations is challenging, as measurements and inversion methods are sensitive to not only the imprint local and large-scale fluxes, but also mesoscale and synoptic-scale atmospheric transport. Quantifying the fine-scale variability in XCO2 from mesoscale and synoptic-scale atmospheric transport will likely improve overall error estimates from flux inversions by improving estimates of representation errors that occur when XCO2 observations are compared to modeled XCO2 in relatively coarse transport models. Here, we utilize various statistical methods to quantify the imprint of atmospheric transport on XCO2 observations. We compare spatial variations along Orbiting Carbon Observatory (OCO-2) satellite tracks to temporal variations observed by the Total Column Carbon Observing Network (TCCON). We observe a coherent seasonal cycle of both within-day temporal and fine-scale spatial variability (of order 10 km) of XCO2 from these two datasets, suggestive of the imprint of mesoscale systems. To account for other potential sources of error in XCO2 retrieval, we compare observed temporal and spatial variations of XCO2 to high-resolution output from the Weather Research and Forecasting (WRF) model run at 9 km resolution. In both simulations and observations, the Northern hemisphere mid-latitude XCO2 showed peak variability during the growing season when atmospheric gradients are largest. These results are qualitatively consistent with our expectations of seasonal variations of the imprint of synoptic and mesoscale atmospheric transport on XCO2 observations; suggesting that these statistical methods could be sensitive to the imprint of atmospheric transport on XCO2 observations.
[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.
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.
Spatial Downscaling of Alien Species Presences using Machine Learning
NASA Astrophysics Data System (ADS)
Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides
2017-07-01
Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.
NASA Technical Reports Server (NTRS)
Gille, Sarah T.
1995-01-01
Geosat altimeter data and numerical model output are used to examine the circulation and dynamics of the Antarctic Circumpolar Current (ACC). The mean sea surface height across the ACC has been reconstructed from height variability measured by the altimeter, without assuming prior knowledge of the geoid. The results indicate locations for the Subantarctic and Polar Fronts which are consistent with in situ observations and indicate that the fronts are substantially steered by bathymetry. Detailed examination of spatial and temporal variability indicates a spatial decorrelation scale of 85 km and a temporal e-folding scale of 34 days. Empirical Orthogonal Function analysis suggests that the scales of motion are relatively short, occuring on 1000 km length-scales rather than basin or global scales. The momentum balance of the ACC has been investigated using output from the high resolution primitive equation model in combination with altimeter data. In the Semtner-Chervin quarter-degree general circulation model topographic form stress is the dominant process balancing the surface wind forcing. In stream coordinates, the dominant effect transporting momentum across the ACC is bibarmonic friction. Potential vorticity is considered on Montgomery streamlines in the model output and along surface streamlines in model and altimeter data. (AN)
Solar Wind Speed Structure in the Inner Corona at 3-12 Ro
NASA Technical Reports Server (NTRS)
Woo, Richard
1995-01-01
Estimates of solar wind speed obtained by Armstrong et al. [1986] based on 1983 VLA multiple-station intensity scintillation measurements inside 12 R(sub o) have been correlated with the electron density structure observed in white-light coronagraph measurements. The observed large- scale and apparently systematic speed variations are found to depend primarily on changes in heliographic latitude and longitude, which leads to the first results on large-scale speed structure in the acceleration region of the solar wind. Over an equatorial hole, solar wind speed is relatively steady, with peak-to-peak variations of 50 km/s and an average of 230 km/s. In contrast, the near-Sun flow speed across the streamer belt shows regular large-scale variations in the range of 100-300 km/s. Based on four groups of data, the gradient is 36 km/s per degree in heliocentric coordinates (corresponding to a rise of 260 km/s over a spatial distance on the Sun of two arcmin) with a standard deviation of 2.4 km/s per degree. The lowest speeds most likely coincide with the stalks of coronal streamers observed in white-light measurements. The detection of significant wind shear over the streamer belt is consistent with in situ and scintillation measurements showing that the density spectrum has a power-law form characteristic of fully developed turbulence over a much broader range of scales than in neighboring regions.
NASA Astrophysics Data System (ADS)
Altenau, Elizabeth H.; Pavelsky, Tamlin M.; Moller, Delwyn; Lion, Christine; Pitcher, Lincoln H.; Allen, George H.; Bates, Paul D.; Calmant, Stéphane; Durand, Michael; Neal, Jeffrey C.; Smith, Laurence C.
2017-04-01
Anabranching rivers make up a large proportion of the world's major rivers, but quantifying their flow dynamics is challenging due to their complex morphologies. Traditional in situ measurements of water levels collected at gauge stations cannot capture out of bank flows and are limited to defined cross sections, which presents an incomplete picture of water fluctuations in multichannel systems. Similarly, current remotely sensed measurements of water surface elevations (WSEs) and slopes are constrained by resolutions and accuracies that limit the visibility of surface waters at global scales. Here, we present new measurements of river WSE and slope along the Tanana River, AK, acquired from AirSWOT, an airborne analogue to the Surface Water and Ocean Topography (SWOT) mission. Additionally, we compare the AirSWOT observations to hydrodynamic model outputs of WSE and slope simulated across the same study area. Results indicate AirSWOT errors are significantly lower than model outputs. When compared to field measurements, RMSE for AirSWOT measurements of WSEs is 9.0 cm when averaged over 1 km squared areas and 1.0 cm/km for slopes along 10 km reaches. Also, AirSWOT can accurately reproduce the spatial variations in slope critical for characterizing reach-scale hydraulics, while model outputs of spatial variations in slope are very poor. Combining AirSWOT and future SWOT measurements with hydrodynamic models can result in major improvements in model simulations at local to global scales. Scientists can use AirSWOT measurements to constrain model parameters over long reach distances, improve understanding of the physical processes controlling the spatial distribution of model parameters, and validate models' abilities to reproduce spatial variations in slope. Additionally, AirSWOT and SWOT measurements can be assimilated into lower-complexity models to try and approach the accuracies achieved by higher-complexity models.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chasapis, Alexandros; Matthaeus, W. H.; Parashar, T. N.
Using data from the Magnetospheric Multiscale (MMS) and Cluster missions obtained in the solar wind, we examine second-order and fourth-order structure functions at varying spatial lags normalized to ion inertial scales. The analysis includes direct two-spacecraft results and single-spacecraft results employing the familiar Taylor frozen-in flow approximation. Several familiar statistical results, including the spectral distribution of energy, and the sale-dependent kurtosis, are extended down to unprecedented spatial scales of ∼6 km, approaching electron scales. The Taylor approximation is also confirmed at those small scales, although small deviations are present in the kinetic range. The kurtosis is seen to attain verymore » high values at sub-proton scales, supporting the previously reported suggestion that monofractal behavior may be due to high-frequency plasma waves at kinetic scales.« less
Satellites and Human Health: Potential for Tracking Cholera Outbreaks
NASA Astrophysics Data System (ADS)
Jutla, A. S.; Akanda, A. S.; Islam, S.
2009-12-01
Cholera continues to be a significant health threat across the globe. The pattern and magnitude of the seven global pandemics suggest that cholera outbreaks primarily originate in coastal regions and spread inland through secondary means. Cholera bacteria show strong association with zooplankton and phytoplankton abundance in coastal ecosystems. Characterization of space-time variability of chlorophyll, a surrogate for phytoplankton abundance, in Northern Bay of Bengal (BoB) is an essential step to develop any methodology for tracking cholera in the Bengal Delta from space. Using ten years of satellite data, this study (a) quantifies the space-time distribution of chlorophyll in BoB region and (b) presents a hypothesis as to how coastal plankton may be related with cholera outbreaks. Preliminary results suggest that variability of chlorophyll at daily scale, irrespective of spatial averaging, resembles white noise. At a monthly scale, chlorophyll shows distinct annual seasonality and chlorophyll values are significantly higher close to the coast than those in the offshore regions. At pixel level (9 km) on monthly scale, on the other hand, chlorophyll does not exhibit much persistence in time. With increased spatial averaging, temporal persistence of monthly chlorophyll increases and lag one autocorrelation stabilizes around 0.60 for 1200 km2 or larger areal averages. Spatial analyses of chlorophyll suggest that coastal region in BoB have a stable sill at 100 km range. Using satellite chlorophyll data, we observe that phytoplankton blooms occur every year in BoB, yet severe cholera outbreaks happen in certain years. This study provides a working hypothesis on how BoB coastal plankton blooms aided by regional hydroclimatic processes may lead to possible cholera outbreaks in Bengal Delta.
Land Cover Change in Colombia: Surprising Forest Recovery Trends between 2001 and 2010
Sánchez-Cuervo, Ana María; Aide, T. Mitchell; Clark, Matthew L.; Etter, Andrés
2012-01-01
Background Monitoring land change at multiple spatial scales is essential for identifying hotspots of change, and for developing and implementing policies for conserving biodiversity and habitats. In the high diversity country of Colombia, these types of analyses are difficult because there is no consistent wall-to-wall, multi-temporal dataset for land-use and land-cover change. Methodology/Principal Findings To address this problem, we mapped annual land-use and land-cover from 2001 to 2010 in Colombia using MODIS (250 m) products coupled with reference data from high spatial resolution imagery (QuickBird) in Google Earth. We used QuickBird imagery to visually interpret percent cover of eight land cover classes used for classifier training and accuracy assessment. Based on these maps we evaluated land cover change at four spatial scales country, biome, ecoregion, and municipality. Of the 1,117 municipalities, 820 had a net gain in woody vegetation (28,092 km2) while 264 had a net loss (11,129 km2), which resulted in a net gain of 16,963 km2 in woody vegetation at the national scale. Woody regrowth mainly occurred in areas previously classified as mixed woody/plantation rather than agriculture/herbaceous. The majority of this gain occurred in the Moist Forest biome, within the montane forest ecoregions, while the greatest loss of woody vegetation occurred in the Llanos and Apure-Villavicencio ecoregions. Conclusions The unexpected forest recovery trend, particularly in the Andes, provides an opportunity to expand current protected areas and to promote habitat connectivity. Furthermore, ecoregions with intense land conversion (e.g. Northern Andean Páramo) and ecoregions under-represented in the protected area network (e.g. Llanos, Apure-Villavicencio Dry forest, and Magdalena-Urabá Moist forest ecoregions) should be considered for new protected areas. PMID:22952816
Detection of large-scale concentric gravity waves from a Chinese airglow imager network
NASA Astrophysics Data System (ADS)
Lai, Chang; Yue, Jia; Xu, Jiyao; Yuan, Wei; Li, Qinzeng; Liu, Xiao
2018-06-01
Concentric gravity waves (CGWs) contain a broad spectrum of horizontal wavelengths and periods due to their instantaneous localized sources (e.g., deep convection, volcanic eruptions, or earthquake, etc.). However, it is difficult to observe large-scale gravity waves of >100 km wavelength from the ground for the limited field of view of a single camera and local bad weather. Previously, complete large-scale CGW imagery could only be captured by satellite observations. In the present study, we developed a novel method that uses assembling separate images and applying low-pass filtering to obtain temporal and spatial information about complete large-scale CGWs from a network of all-sky airglow imagers. Coordinated observations from five all-sky airglow imagers in Northern China were assembled and processed to study large-scale CGWs over a wide area (1800 km × 1 400 km), focusing on the same two CGW events as Xu et al. (2015). Our algorithms yielded images of large-scale CGWs by filtering out the small-scale CGWs. The wavelengths, wave speeds, and periods of CGWs were measured from a sequence of consecutive assembled images. Overall, the assembling and low-pass filtering algorithms can expand the airglow imager network to its full capacity regarding the detection of large-scale gravity waves.
A Model-based Approach to Scaling GPP and NPP in Support of MODIS Land Product Validation
NASA Astrophysics Data System (ADS)
Turner, D. P.; Cohen, W. B.; Gower, S. T.; Ritts, W. D.
2003-12-01
Global products from the Earth-orbiting MODIS sensor include land cover, leaf area index (LAI), FPAR, 8-day gross primary production (GPP), and annual net primary production (NPP) at the 1 km spatial resolution. The BigFoot Project was designed specifically to validate MODIS land products, and has initiated ground measurements at 9 sites representing a wide array of vegetation types. An ecosystem process model (Biome-BGC) is used to generate estimates of GPP and NPP for each 5 km x 5 km BigFoot site. Model inputs include land cover and LAI (from Landsat ETM+), daily meteorological data (from a centrally located eddy covariance flux tower), and soil characteristics. Model derived outputs are validated against field-measured NPP and flux tower-derived GPP. The resulting GPP and NPP estimates are then aggregated to the 1 km resolution for direct spatial comparison with corresponding MODIS products. At the high latitude sites (tundra and boreal forest), the MODIS GPP phenology closely tracks the BigFoot GPP, but there is a high bias in the MODIS GPP. In the temperate zone sites, problems with the timing and magnitude of the MODIS FPAR introduce differences in MODIS GPP compared to the validation data at some sites. However, the MODIS LAI/FPAR data are currently being reprocessed (=Collection 4) and new comparisons will be made for 2002. The BigFoot scaling approach permits precise overlap in spatial and temporal resolution between the MODIS products and BigFoot products, and thus permits the evaluation of specific components of the MODIS NPP algorithm. These components include meteorological inputs from the NASA Data Assimilation Office, LAI and FPAR from other MODIS algorithms, and biome-specific parameters for base respiration rate and light use efficiency.
NASA Astrophysics Data System (ADS)
Cao, X.; Tian, F.; Telford, R.; Ni, J.; Xu, Q.; Chen, F.; Liu, X.; Stebich, M.; Zhao, Y.; Herzschuh, U.
2017-12-01
Pollen-based quantitative reconstructions of past climate variables is a standard palaeoclimatic approach. Despite knowing that the spatial extent of the calibration-set affects the reconstruction result, guidance is lacking as to how to determine a suitable spatial extent of the pollen-climate calibration-set. In this study, past mean annual precipitation (Pann) during the Holocene (since 11.5 cal ka BP) is reconstructed repeatedly for pollen records from Qinghai Lake (36.7°N, 100.5°E; north-east Tibetan Plateau), Gonghai Lake (38.9°N, 112.2°E; north China) and Sihailongwan Lake (42.3°N, 126.6°E; north-east China) using calibration-sets of varying spatial extents extracted from the modern pollen dataset of China and Mongolia (2559 sampling sites and 168 pollen taxa in total). Results indicate that the spatial extent of the calibration-set has a strong impact on model performance, analogue quality and reconstruction diagnostics (absolute value, range, trend, optimum). Generally, these effects are stronger with the modern analogue technique (MAT) than with weighted averaging partial least squares (WA-PLS). With respect to fossil spectra from northern China, the spatial extent of calibration-sets should be restricted to ca. 1000 km in radius because small-scale calibration-sets (<800 km radius) will likely fail to include enough spatial variation in the modern pollen assemblages to reflect the temporal range shifts during the Holocene, while too broad a scale calibration-set (>1500 km radius) will include taxa with very different pollen-climate relationships. Based on our results we conclude that the optimal calibration-set should 1) cover a reasonably large spatial extent with an even distribution of modern pollen samples; 2) possess good model performance as indicated by cross-validation, high analogue quality, and excellent fit with the target fossil pollen spectra; 3) possess high taxonomic resolution, and 4) obey the modern and past distribution ranges of taxa inferred from palaeo-genetic and macrofossil studies.
NASA Astrophysics Data System (ADS)
Roelfsema, C. M.; Phinn, S. R.; Lyons, M. B.; Kovacs, E.; Saunders, M. I.; Leon, J. X.
2013-12-01
Corals and Submerged Aquatic Vegetation (SAV) are typically found in highly dynamic environments where the magnitude and types of physical and biological processes controlling their distribution, diversity and function changes dramatically. Recent advances in the types of satellite image data and the length of their archives that are available globally, coupled with new techniques for extracting environmental information from these data sets has enabled significant advances to be made in our ability to map and monitor coral and SAV environments. Object Based Image Analysis techniques are one of the most significant advances in information extraction techniques for processing images to deliver environmental information at multiple spatial scales. This poster demonstrates OBIA applied to high spatial resolution satellite image data to map and monitor coral and SAV communities across a variety of environments in the Western Pacific that vary in their extent, biological composition, forcing physical factors and location. High spatial resolution satellite imagery (Quickbird, Ikonos and Worldview2) were acquired coincident with field surveys on each reef to collect georeferenced benthic photo transects, over various areas in the Western Pacific. Base line maps were created, from Roviana Lagoon Solomon island (600 km2), Bikini Atoll Marshall Island (800 Km2), Lizard Island, Australia (30 km2) and time series maps for geomorphic and benthic communities were collected for Heron Reef, Australia (24 km2) and Eastern Banks area of Moreton Bay, Australia (200 km2). The satellite image data were corrected for radiometric and atmospheric distortions to at-surface reflectance. Georeferenced benthic photos were acquired by divers or Autonomous Underwater Vehicles, analysed for benthic cover composition, and used for calibration and validation purposes. Hierarchical mapping from: reef/non-reef (1000's - 10000's m); reef type (100's - 1000's m); 'geomorphic zone' (10's - 100's m); to dominant components of benthic cover compositions (1 - 10's m); and individual benthic cover type scale (0.5-5.0's m), was completed using object based segmentation and semi-automated labelling through membership rules. Accuracy assessment of the satellite image based maps and field data sets scales maps produced with 90% maximum accuracy larger scales and less complex maps, versus 40 % at smaller scale and complex maps. The study showed that current data sets and object based analysis are able to reliable map at various scales and level of complexity covering a variety of extent and environments at various times; as a result science and management can use these tools to assess and understand the ecological processes taking place in coral and SAV environments.
Macroecological factors shape local-scale spatial patterns in agriculturalist settlements.
Tao, Tingting; Abades, Sebastián; Teng, Shuqing; Huang, Zheng Y X; Reino, Luís; Chen, Bin J W; Zhang, Yong; Xu, Chi; Svenning, Jens-Christian
2017-11-15
Macro-scale patterns of human systems ranging from population distribution to linguistic diversity have attracted recent attention, giving rise to the suggestion that macroecological rules shape the assembly of human societies. However, in which aspects the geography of our own species is shaped by macroecological factors remains poorly understood. Here, we provide a first demonstration that macroecological factors shape strong local-scale spatial patterns in human settlement systems, through an analysis of spatial patterns in agriculturalist settlements in eastern mainland China based on high-resolution Google Earth images. We used spatial point pattern analysis to show that settlement spatial patterns are characterized by over-dispersion at fine spatial scales (0.05-1.4 km), consistent with territory segregation, and clumping at coarser spatial scales beyond the over-dispersion signals, indicating territorial clustering. Statistical modelling shows that, at macroscales, potential evapotranspiration and topographic heterogeneity have negative effects on territory size, but positive effects on territorial clustering. These relationships are in line with predictions from territory theory for hunter-gatherers as well as for many animal species. Our results help to disentangle the complex interactions between intrinsic spatial processes in agriculturalist societies and external forcing by macroecological factors. While one may speculate that humans can escape ecological constraints because of unique abilities for environmental modification and globalized resource transportation, our work highlights that universal macroecological principles still shape the geography of current human agricultural societies. © 2017 The Author(s).
NASA Astrophysics Data System (ADS)
Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung
2017-04-01
Soil moisture is one of the most important keys for understanding regional and global climate systems. Soil moisture is directly related to agricultural processes as well as hydrological processes because soil moisture highly influences vegetation growth and determines water supply in the agroecosystem. Accurate monitoring of the spatiotemporal pattern of soil moisture is important. Soil moisture has been generally provided through in situ measurements at stations. Although field survey from in situ measurements provides accurate soil moisture with high temporal resolution, it requires high cost and does not provide the spatial distribution of soil moisture over large areas. Microwave satellite (e.g., advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR2), the Advanced Scatterometer (ASCAT), and Soil Moisture Active Passive (SMAP)) -based approaches and numerical models such as Global Land Data Assimilation System (GLDAS) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) provide spatial-temporalspatiotemporally continuous soil moisture products at global scale. However, since those global soil moisture products have coarse spatial resolution ( 25-40 km), their applications for agriculture and water resources at local and regional scales are very limited. Thus, soil moisture downscaling is needed to overcome the limitation of the spatial resolution of soil moisture products. In this study, GLDAS soil moisture data were downscaled up to 1 km spatial resolution through the integration of AMSR2 and ASCAT soil moisture data, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Moderate Resolution Imaging Spectroradiometer (MODIS) data—Land Surface Temperature, Normalized Difference Vegetation Index, and Land cover—using modified regression trees over East Asia from 2013 to 2015. Modified regression trees were implemented using Cubist, a commercial software tool based on machine learning. An optimization based on pruning of rules derived from the modified regression trees was conducted. Root Mean Square Error (RMSE) and Correlation coefficients (r) were used to optimize the rules, and finally 59 rules from modified regression trees were produced. The results show high validation r (0.79) and low validation RMSE (0.0556m3/m3). The 1 km downscaled soil moisture was evaluated using ground soil moisture data at 14 stations, and both soil moisture data showed similar temporal patterns (average r=0.51 and average RMSE=0.041). The spatial distribution of the 1 km downscaled soil moisture well corresponded with GLDAS soil moisture that caught both extremely dry and wet regions. Correlation between GLDAS and the 1 km downscaled soil moisture during growing season was positive (mean r=0.35) in most regions.
NASA Astrophysics Data System (ADS)
Kim, Y.; Du, J.; Kimball, J. S.
2017-12-01
The landscape freeze-thaw (FT) status derived from satellite microwave remote sensing is closely linked to vegetation phenology and productivity, surface energy exchange, evapotranspiration, snow/ice melt dynamics, and trace gas fluxes over land areas affected by seasonally frozen temperatures. A long-term global satellite microwave Earth System Data Record of daily landscape freeze-thaw status (FT-ESDR) was developed using similar calibrated 37GHz, vertically-polarized (V-pol) brightness temperatures (Tb) from SMMR, SSM/I, and SSMIS sensors. The FT-ESDR shows mean annual spatial classification accuracies of 90.3 and 84.3 % for PM and AM overpass retrievals relative surface air temperature (SAT) measurement based FT estimates from global weather stations. However, the coarse FT-ESDR gridding (25-km) is insufficient to distinguish finer scale FT heterogeneity. In this study, we tested alternative finer scale FT estimates derived from two enhanced polar-grid (3.125-km and 6-km resolution), 36.5 GHz V-pol Tb records derived from calibrated AMSR-E and AMSR2 sensor observations. The daily FT estimates are derived using a modified seasonal threshold algorithm that classifies daily Tb variations in relation to grid cell-wise FT thresholds calibrated using ERA-Interim reanalysis based SAT, downscaled using a digital terrain map and estimated temperature lapse rates. The resulting polar-grid FT records for a selected study year (2004) show mean annual spatial classification accuracies of 90.1% (84.2%) and 93.1% (85.8%) for respective PM (AM) 3.125km and 6-km Tb retrievals relative to in situ SAT measurement based FT estimates from regional weather stations. Areas with enhanced FT accuracy include water-land boundaries and mountainous terrain. Differences in FT patterns and relative accuracy obtained from the enhanced grid Tb records were attributed to several factors, including different noise contributions from underlying Tb processing and spatial mismatches between Tb retrievals and SAT calibrated FT thresholds.
NASA Astrophysics Data System (ADS)
Hansen, A. L.; Donnelly, C.; Refsgaard, J. C.; Karlsson, I. B.
2018-01-01
This paper describes a modeling approach proposed to simulate the impact of local-scale, spatially targeted N-mitigation measures for the Baltic Sea Basin. Spatially targeted N-regulations aim at exploiting the considerable spatial differences in the natural N-reduction taking place in groundwater and surface water. While such measures can be simulated using local-scale physically-based catchment models, use of such detailed models for the 1.8 million km2 Baltic Sea basin is not feasible due to constraints on input data and computing power. Large-scale models that are able to simulate the Baltic Sea basin, on the other hand, do not have adequate spatial resolution to simulate some of the field-scale measures. Our methodology combines knowledge and results from two local-scale physically-based MIKE SHE catchment models, the large-scale and more conceptual E-HYPE model, and auxiliary data in order to enable E-HYPE to simulate how spatially targeted regulation of agricultural practices may affect N-loads to the Baltic Sea. We conclude that the use of E-HYPE with this upscaling methodology enables the simulation of the impact on N-loads of applying a spatially targeted regulation at the Baltic Sea basin scale to the correct order-of-magnitude. The E-HYPE model together with the upscaling methodology therefore provides a sound basis for large-scale policy analysis; however, we do not expect it to be sufficiently accurate to be useful for the detailed design of local-scale measures.
Accumulation patterns around Dome C, East Antarctica, in the last 73 kyr
NASA Astrophysics Data System (ADS)
Cavitte, Marie G. P.; Parrenin, Frédéric; Ritz, Catherine; Young, Duncan A.; Van Liefferinge, Brice; Blankenship, Donald D.; Frezzotti, Massimo; Roberts, Jason L.
2018-04-01
We reconstruct the pattern of surface accumulation in the region around Dome C, East Antarctica, since the last glacial. We use a set of 18 isochrones spanning all observable depths of the ice column, interpreted from various ice-penetrating radar surveys and a 1-D ice flow model to invert for accumulation rates in the region. The shallowest four isochrones are then used to calculate paleoaccumulation rates between isochrone pairs using a 1-D assumption where horizontal advection is negligible in the time interval of each layer. We observe that the large-scale (100s km) surface accumulation gradient is spatially stable through the last 73 kyr, which reflects current modeled and observed precipitation gradients in the region. We also observe small-scale (10 s km) accumulation variations linked to snow redistribution at the surface, due to changes in its slope and curvature in the prevailing wind direction that remain spatially stationary since the last glacial.
NASA Astrophysics Data System (ADS)
Molero, B.; Leroux, D. J.; Richaume, P.; Kerr, Y. H.; Merlin, O.; Cosh, M. H.; Bindlish, R.
2018-01-01
We conduct a novel comprehensive investigation that seeks to prove the connection between spatial scales and timescales in surface soil moisture (SM) within the satellite footprint ( 50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies at timescales ranging from 0.5 to 128 days, using wavelet transforms. Then, their degree of spatial representativeness is evaluated on a per-timescale basis by comparison to large spatial scale data sets (the in situ spatial average, SMOS, AMSR2, and ECMWF). Four methods are used for this: temporal stability analysis (TStab), triple collocation (TC), percentage of correlated areas (CArea), and a new proposed approach that uses wavelet-based correlations (WCor). We found that the mean of the spatial representativeness values tends to increase with the timescale but so does their dispersion. Locations exhibit poor spatial representativeness at scales below 4 days, while either very good or poor representativeness at seasonal scales. Regarding the methods, TStab cannot be applied to the anomaly series due to their multiple zero-crossings, and TC is suitable for week and month scales but not for other scales where data set cross-correlations are found low. In contrast, WCor and CArea give consistent results at all timescales. WCor is less sensitive to the spatial sampling density, so it is a robust method that can be applied to sparse networks (one station per footprint). These results are promising to improve the validation and downscaling of satellite SM series and the optimization of SM networks.
A High-Resolution Aerosol Retrieval Method for Urban Areas Using MISR Data
NASA Astrophysics Data System (ADS)
Moon, T.; Wang, Y.; Liu, Y.; Yu, B.
2012-12-01
Satellite-retrieved Aerosol Optical Depth (AOD) can provide a cost-effective way to monitor particulate air pollution without using expensive ground measurement sensors. One of the current state-of-the-art AOD retrieval method is NASA's Multi-angle Imaging SpectroRadiometer (MISR) operational algorithm, which has the spatial resolution of 17.6 km x 17.6 km. While the MISR baseline scheme already leads to exciting research opportunities to study particle compositions at regional scale, its spatial resolution is too coarse for analyzing urban areas where the AOD level has stronger spatial variations. We develop a novel high-resolution AOD retrieval algorithm that still uses MISR's radiance observations but has the resolution of 4.4km x 4.4km. We achieve the high resolution AOD retrieval by implementing a hierarchical Bayesian model and Monte-Carlo Markov Chain (MCMC) inference method. Our algorithm not only improves the spatial resolution, but also extends the coverage of AOD retrieval and provides with additional composition information of aerosol components that contribute to the AOD. We validate our method using the recent NASA's DISCOVER-AQ mission data, which contains the ground measured AOD values for Washington DC and Baltimore area. The validation result shows that, compared to the operational MISR retrievals, our scheme has 41.1% more AOD retrieval coverage for the DISCOVER-AQ data points and 24.2% improvement in mean-squared error (MSE) with respect to the AERONET ground measurements.
L-band Soil Moisture Mapping using Small UnManned Aerial Systems
NASA Astrophysics Data System (ADS)
Dai, E.; Gasiewski, A. J.; Stachura, M.; Elston, J.; Venkitasubramony, A.
2016-12-01
1. IntroductionSoil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions as low as 5 km for some products. However, there exists a need for measurements of soil moisture on smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform). Compared with various other proposed methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling scale studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site on September 8th and 9th, 2015 and Yuma Colorado Irrigation Research Foundation (IRF) site from June to August, 2016. These tests were flown at 25-50 m altitude to obtain differing spatial resolutions. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. 2. References[1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C-Band Microwave Soil Moisture Retrieval During CLASIC 2007," Proc. IGARSS, 2008. [2] Robock, A., S. Steele-Dunne, J. Basara, W. Crow, and M. Moghaddam M, "In Situ Network and Scaling," SMAP Algorithm and Cal/Val Workshop, 2009. [3] Walker, A., "Airborne Microwave Radiometer Measurements During CanEx-SM10," Second SMAP Cal/Val Workshop, 2011.
Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia
NASA Astrophysics Data System (ADS)
Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.
2017-12-01
Recent improvements in satellite instrumentation has increased the resolution and frequency of soil moisture observations, and this in turn has supported the development of higher resolution land surface process models. Calibration and validation of these products is restricted by the mismatch of scales between remotely sensed and contemporary ground based observations. Although the cosmic ray neutron soil moisture probe can provide estimates soil moisture at a scale useful for the calibration and validation purposes, it is spatially limited to a single, fixed location. This scaling issue has been addressed with the development of mobile soil moisture monitoring systems that utilizes the cosmic ray neutron method, typically referred to as a `rover'. This manuscript describes a project designed to develop approaches for undertaking rover surveys to produce soil moisture estimates at scales comparable to satellite observations and land surface process models. A custom designed, trailer-mounted rover was used to conduct repeat surveys at two scales in the Mallee region of Victoria, Australia. A broad scale survey was conducted at 36 x 36 km covering an area of a standard SMAP pixel and an intensive scale survey was conducted over a 10 x 10 km portion of the broad scale survey, which is at a scale equivalent to that used for national water balance modelling. We will describe the design of the rover, the methods used for converting neutron counts into soil moisture and discuss factors controlling soil moisture variability. We found that the intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution and the broad scale at 9 km resolution. We conclude that these products are well suited for future analysis of satellite soil moisture retrievals and finer scale soil moisture models.
The three scales of submarine groundwater flow and discharge across passive continental margins
Bratton, John F.
2010-01-01
Increased study of submarine groundwater systems in recent years has provided a wealth of new data and techniques, but some ambiguity has been introduced by insufficient distinguishing of the relevant spatial scales of the phenomena studied. Submarine groundwater flow and discharge on passive continental margins can be most productively studied and discussed by distinct consideration of the following three spatial scales: (1) the nearshore scale, spanning approximately 0–10 m offshore and including the unconfined surficial aquifer; (2) the embayment scale, spanning approximately 10 m to as much as 10 km offshore and including the first confined submarine aquifer and its terminus; and (3) the shelf scale, spanning the width and thickness of the aquifers of the entire continental shelf, from the base of the first confined aquifer downward to the basement, and including influences of geothermal convection and glacio-eustatic change in sea level.
Internal variability of a dynamically downscaled climate over North America
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Jiali; Bessac, Julie; Kotamarthi, Rao
This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble duringmore » the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.« less
Internal variability of a dynamically downscaled climate over North America
NASA Astrophysics Data System (ADS)
Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth
2018-06-01
This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.
Internal variability of a dynamically downscaled climate over North America
NASA Astrophysics Data System (ADS)
Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth
2017-09-01
This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.
NASA Astrophysics Data System (ADS)
Liang, J.; Gurney, K. R.; O'Keeffe, D.; Patarasuk, R.; Hutchins, M.; Rao, P.
2017-12-01
Spatially-resolved fossil fuel CO2 (FFCO2) emissions are used not only in complex atmospheric modeling systems as prior scenarios to simulate concentrations of CO2 in the atmosphere, but to improve understanding of relationships with socioeconomic factors in support of sustainability policymaking. We present a comparison of ODIAC, a top-down global gridded FFCO2 emissions dataset, and Hesita, a bottom-up FFCO2 emissions dataset, in four US cities, including Los Angles, Indianapolis, Salt Lake City and Baltimore City. ODIAC was developed by downscaling national total emissions to 1km-by-1km grid cells using satellite nightlight imagery as proxy. Hesita was built from the ground up by allocating sector-specific county-level emissions to urban-level spatial surrogates including facility locations, road maps, building footprints/parcels, railroad maps and shipping lanes. The differences in methodology and data sources could lead to large discrepancies in FFCO2 estimates at the urban scale, and these discrepancies need to be taken into account in conducting atmospheric modeling or socioeconomic analysis. This comparison work is aimed at quantifying the statistical and spatial difference between the two FFCO2 inventories. An analysis of the difference in total emissions, spatial distribution and statistical distribution resulted in the following findings: (1) ODIAC agrees well with Hestia in total FFCO2 emissions estimates across the four cities with a difference from 3%-20%; (2) Small-scale areal and linear spatial features such as roads and buildings are either entirely missing or not very well represented in ODIAC, since nightlight imagery might not be able to capture these information. This might further lead to underestimated on-road FFCO2 emissions in ODIAC; (3) The statistical distribution of ODIAC is more concentrated around the mean with much less samples in the lower range. These phenomena could result from the nightlight halo and saturation effects; (4) The grid-cell cumulative emissions of ODIAC appear in good agreement with that of Hestia, implying the two inventories have similar overall spatial structures at the city scale.
NASA Astrophysics Data System (ADS)
Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.
2017-12-01
Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.
NASA Astrophysics Data System (ADS)
Huret, M.; Petitgas, P.; Woillez, M.
2010-10-01
Dispersal of fish early life stages explains part of the recruitment success, through interannual variability in spawning, transport and survival. Dispersal results from a complex interaction between physical and biological processes acting at different temporal and spatial scales, and at the individual or population level. In this paper we quantify the response of anchovy egg and larval dispersal in the Bay of Biscay to the following sources of variability: vertical larval behaviour, drift duration, adult spawning location and timing, and spatio-temporal variability in the hydrodynamics. We use simulations of Lagrangian trajectories in a 3-dimensional hydrodynamic model, as well as spatial indices describing different properties of the dispersal kernel: the mean transport (distance, direction), its variance, occupation of space by particles and their aggregation. We show that larval drift duration has a major impact on the dispersion at scales of ˜100 km, but that vertical behaviour becomes dominant reducing dispersion at scales of ˜1-10 km. Spawning location plays a major role in explaining connectivity patterns, in conjunction with spawning temporal variability. Interannual variability in the circulation dominates over seasonal variability. However, seasonal patterns become predominant for coastal spawning locations, revealing a recurrent shift in the direction of dispersal during the anchovy spawning season.
In-situ observation of atmospheric particulates
NASA Astrophysics Data System (ADS)
Harrison, William Alan
Airborne particulates play a central role in both the earth’s radiation balance and as a trigger for a wide range of health impacts. Air quality monitors are placed in networks across many cities globally. Typically these provide at best a few recording locations per city. However, large spatial variability occurs on the neighborhood scale. This study sets out to comprehensively characterize a full size distribution from 0.25 - 32 μm of airborne particulates on a fine spatial scale (meters). To fully characterize the impact of atmospheric particulates, global scale observations and data products are needed. Satellite products allow for this global coverage but require in situ validations. For the first part of this study data is gathered on a near daily basis over the month of May, 2014 in a 100 km2 area encompassing parts of Richardson, Texas, and Garland, Texas. Wind direction was determined to be the dominant factor in classifying the data. The highest mean PM2.5 concentration was 14.1 ± 5.7 μgm. -3 corresponding to periods when the wind was out of the south. The lowest PM2.5 concentrations were observed after several consecutive days of rainfall. The rainfall was found to not only “cleanse” the air, leaving a mean PM2.5 concentration as low as 3.0 ± 0.5 μgm. -3 , but to leave the region with a more uniform PM2.5 concentration. Variograms were used to determine an appropriate spatial scale for future sensor placement to provide measurements on a neighborhood scale and found that the spatial scales varied, depending on the synoptic weather pattern, from 0.8 km to 5.2 km, with a typical length scale of 1.7 km. This second part of this study used a zero emission remote-controlled aerial vehicle to look at the horizontal, vertical, and temporal variability of airborne particulates within the first 140 m of the atmosphere. Four flights where conducted on December 4, 2014 between 12:00 pm and 5:00 pm local time. The first three flights flew a pattern of increasing altitude up to 140 m. The fourth flight was conducted at a near constant altitude of 60 m. The mean PM2.5 concentration for the three flights with varying altitude was 36.3 μgm. -3, with the highest concentration occurring below 10 m altitude. The overall vertical variation was very small with a standard deviation of only 3.6 μgm. -3. PM2.5 concentration also did not change much throughout the day with mean concentrations for the altitude-varying flights of 35.1, 37.2, and 36.8 μgm. -3, respectively. The fourth flight, flown at a near constant altitude, had a lower concentration of 23.5 μgm. -3.
NASA Astrophysics Data System (ADS)
Flores, Alejandro N.; Bras, Rafael L.; Entekhabi, Dara
2012-08-01
Soil moisture information is critical for applications like landslide susceptibility analysis and military trafficability assessment. Existing technologies cannot observe soil moisture at spatial scales of hillslopes (e.g., 100 to 102 m) and over large areas (e.g., 102 to 105 km2) with sufficiently high temporal coverage (e.g., days). Physics-based hydrologic models can simulate soil moisture at the necessary spatial and temporal scales, albeit with error. We develop and test a data assimilation framework based on the ensemble Kalman filter for constraining uncertain simulated high-resolution soil moisture fields to anticipated remote sensing products, specifically NASA's Soil Moisture Active-Passive (SMAP) mission, which will provide global L band microwave observation approximately every 2-3 days. The framework directly assimilates SMAP synthetic 3 km radar backscatter observations to update hillslope-scale bare soil moisture estimates from a physics-based model. Downscaling from 3 km observations to hillslope scales is achieved through the data assimilation algorithm. Assimilation reduces bias in near-surface soil moisture (e.g., top 10 cm) by approximately 0.05 m3/m3and expected root-mean-square errors by at least 60% in much of the watershed, relative to an open loop simulation. However, near-surface moisture estimates in channel and valley bottoms do not improve, and estimates of profile-integrated moisture throughout the watershed do not substantially improve. We discuss the implications of this work, focusing on ongoing efforts to improve soil moisture estimation in the entire soil profile through joint assimilation of other satellite (e.g., vegetation) and in situ soil moisture measurements.
Are fractal dimensions of the spatial distribution of mineral deposits meaningful?
Raines, G.L.
2008-01-01
It has been proposed that the spatial distribution of mineral deposits is bifractal. An implication of this property is that the number of deposits in a permissive area is a function of the shape of the area. This is because the fractal density functions of deposits are dependent on the distance from known deposits. A long thin permissive area with most of the deposits in one end, such as the Alaskan porphyry permissive area, has a major portion of the area far from known deposits and consequently a low density of deposits associated with most of the permissive area. On the other hand, a more equi-dimensioned permissive area, such as the Arizona porphyry permissive area, has a more uniform density of deposits. Another implication of the fractal distribution is that the Poisson assumption typically used for estimating deposit numbers is invalid. Based on datasets of mineral deposits classified by type as inputs, the distributions of many different deposit types are found to have characteristically two fractal dimensions over separate non-overlapping spatial scales in the range of 5-1000 km. In particular, one typically observes a local dimension at spatial scales less than 30-60 km, and a regional dimension at larger spatial scales. The deposit type, geologic setting, and sample size influence the fractal dimensions. The consequence of the geologic setting can be diminished by using deposits classified by type. The crossover point between the two fractal domains is proportional to the median size of the deposit type. A plot of the crossover points for porphyry copper deposits from different geologic domains against median deposit sizes defines linear relationships and identifies regions that are significantly underexplored. Plots of the fractal dimension can also be used to define density functions from which the number of undiscovered deposits can be estimated. This density function is only dependent on the distribution of deposits and is independent of the definition of the permissive area. Density functions for porphyry copper deposits appear to be significantly different for regions in the Andes, Mexico, United States, and western Canada. Consequently, depending on which regional density function is used, quite different estimates of numbers of undiscovered deposits can be obtained. These fractal properties suggest that geologic studies based on mapping at scales of 1:24,000 to 1:100,000 may not recognize processes that are important in the formation of mineral deposits at scales larger than the crossover points at 30-60 km. ?? 2008 International Association for Mathematical Geology.
Costantini, Federica; Carlesi, Lorenzo; Abbiati, Marco
2013-01-01
While shallow water red coral populations have been overharvested in the past, nowadays, commercial harvesting shifted its pressure on mesophotic organisms. An understanding of red coral population structure, particularly larval dispersal patterns and connectivity among harvested populations is paramount to the viability of the species. In order to determine patterns of genetic spatial structuring of deep water Corallium rubrum populations, for the first time, colonies found between 58–118 m depth within the Tyrrhenian Sea were collected and analyzed. Ten microsatellite loci and two regions of mitochondrial DNA (mtMSH and mtC) were used to quantify patterns of genetic diversity within populations and to define population structuring at spatial scales from tens of metres to hundreds of kilometres. Microsatellites showed heterozygote deficiencies in all populations. Significant levels of genetic differentiation were observed at all investigated spatial scales, suggesting that populations are likely to be isolated. This differentiation may by the results of biological interactions, occurring within a small spatial scale and/or abiotic factors acting at a larger scale. Mitochondrial markers revealed significant genetic structuring at spatial scales greater then 100 km showing the occurrence of a barrier to gene flow between northern and southern Tyrrhenian populations. These findings provide support for the establishment of marine protected areas in the deep sea and off-shore reefs, in order to effectively maintain genetic diversity of mesophotic red coral populations. PMID:23646109
Costantini, Federica; Carlesi, Lorenzo; Abbiati, Marco
2013-01-01
While shallow water red coral populations have been overharvested in the past, nowadays, commercial harvesting shifted its pressure on mesophotic organisms. An understanding of red coral population structure, particularly larval dispersal patterns and connectivity among harvested populations is paramount to the viability of the species. In order to determine patterns of genetic spatial structuring of deep water Corallium rubrum populations, for the first time, colonies found between 58-118 m depth within the Tyrrhenian Sea were collected and analyzed. Ten microsatellite loci and two regions of mitochondrial DNA (mtMSH and mtC) were used to quantify patterns of genetic diversity within populations and to define population structuring at spatial scales from tens of metres to hundreds of kilometres. Microsatellites showed heterozygote deficiencies in all populations. Significant levels of genetic differentiation were observed at all investigated spatial scales, suggesting that populations are likely to be isolated. This differentiation may by the results of biological interactions, occurring within a small spatial scale and/or abiotic factors acting at a larger scale. Mitochondrial markers revealed significant genetic structuring at spatial scales greater then 100 km showing the occurrence of a barrier to gene flow between northern and southern Tyrrhenian populations. These findings provide support for the establishment of marine protected areas in the deep sea and off-shore reefs, in order to effectively maintain genetic diversity of mesophotic red coral populations.
NASA Astrophysics Data System (ADS)
Torgersen, C. E.; Fullerton, A.; Lawler, J. J.; Ebersole, J. L.; Leibowitz, S. G.; Steel, E. A.; Beechie, T. J.; Faux, R.
2016-12-01
Understanding spatial patterns in water temperature will be essential for evaluating vulnerability of aquatic biota to future climate and for identifying and protecting diverse thermal habitats. We used high-resolution remotely sensed water temperature data for over 16,000 km of 2nd to 7th-order rivers throughout the Pacific Northwest and California to evaluate spatial patterns of summertime water temperature at multiple spatial scales. We found a diverse and geographically distributed suite of whole-river patterns. About half of rivers warmed asymptotically in a downstream direction, whereas the rest exhibited complex and unique spatial patterns. Patterns were associated with both broad-scale hydroclimatic variables as well as characteristics unique to each basin. Within-river thermal heterogeneity patterns were highly river-specific; across rivers, median size and spacing of cool patches <15 °C were around 250 m. Patches of this size are large enough for juvenile salmon rearing and for resting during migration, and the distance between patches is well within the movement capabilities of both juvenile and adult salmon. We found considerable thermal heterogeneity at fine spatial scales that may be important to fish that would be missed if data were analyzed at coarser scales. We estimated future thermal heterogeneity and concluded that climate change will cause warmer temperatures overall, but that thermal heterogeneity patterns may remain similar in the future for many rivers. We demonstrated considerable spatial complexity in both current and future water temperature, and resolved spatial patterns that could not have been perceived without spatially continuous data.
Nijhof, Carl O P; Huijbregts, Mark A J; Golsteijn, Laura; van Zelm, Rosalie
2016-04-01
We compared the influence of spatial variability in environmental characteristics and the uncertainty in measured substance properties of seven chemicals on freshwater fate factors (FFs), representing the residence time in the freshwater environment, and on exposure factors (XFs), representing the dissolved fraction of a chemical. The influence of spatial variability was quantified using the SimpleBox model in which Europe was divided in 100 × 100 km regions, nested in a regional (300 × 300 km) and supra-regional (500 × 500 km) scale. Uncertainty in substance properties was quantified by means of probabilistic modelling. Spatial variability and parameter uncertainty were expressed by the ratio k of the 95%ile and 5%ile of the FF and XF. Our analysis shows that spatial variability ranges in FFs of persistent chemicals that partition predominantly into one environmental compartment was up to 2 orders of magnitude larger compared to uncertainty. For the other (less persistent) chemicals, uncertainty in the FF was up to 1 order of magnitude larger than spatial variability. Variability and uncertainty in freshwater XFs of the seven chemicals was negligible (k < 1.5). We found that, depending on the chemical and emission scenario, accounting for region-specific environmental characteristics in multimedia fate modelling, as well as accounting for parameter uncertainty, can have a significant influence on freshwater fate factor predictions. Therefore, we conclude that it is important that fate factors should not only account for parameter uncertainty, but for spatial variability as well, as this further increases the reliability of ecotoxicological impacts in LCA. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Alavi-Shoushtari, N.; King, D.
2017-12-01
Agricultural landscapes are highly variable ecosystems and are home to many local farmland species. Seasonal, phenological and inter-annual agricultural landscape dynamics have potential to affect the richness and abundance of farmland species. Remote sensing provides data and techniques which enable monitoring landscape changes in multiple temporal and spatial scales. MODIS high temporal resolution remote sensing images enable detection of seasonal and phenological trends, while Landsat higher spatial resolution images, with its long term archive enables inter-annual trend analysis over several decades. The objective of this study to use multi-spatial and multi-temporal remote sensing data to model the response of farmland species to landscape metrics. The study area is the predominantly agricultural region of eastern Ontario. 92 sample landscapes were selected within this region using a protocol designed to maximize variance in composition and configuration heterogeneity while controlling for amount of forest and spatial autocorrelation. Two sample landscape extents (1×1km and 3×3km) were selected to analyze the impacts of spatial scale on biodiversity response. Gamma diversity index data for four taxa groups (birds, butterflies, plants, and beetles) were collected during the summers of 2011 and 2012 within the cropped area of each landscape. To extract the seasonal and phenological metrics a 2000-2012 MODIS NDVI time-series was used, while a 1985-2012 Landsat time-series was used to model the inter-annual trends of change in the sample landscapes. The results of statistical modeling showed significant relationships between farmland biodiversity for several taxa and the phenological and inter-annual variables. The following general results were obtained: 1) Among the taxa groups, plant and beetles diversity was most significantly correlated with the phenological variables; 2) Those phenological variables which are associated with the variability in the start of season date across the sample landscapes and the variability in the corresponding NDVI values at that date showed the strongest correlation with the biodiversity indices; 3) The significance of the models improved when using 3×3km site extent both for MODIS and Landsat based models due most likely to the larger sample size over 3x3km.
Exploratory spatial data analysis of global MODIS active fire data
NASA Astrophysics Data System (ADS)
Oom, D.; Pereira, J. M. C.
2013-04-01
We performed an exploratory spatial data analysis (ESDA) of autocorrelation patterns in the NASA MODIS MCD14ML Collection 5 active fire dataset, for the period 2001-2009, at the global scale. The dataset was screened, resulting in an annual rate of false alarms and non-vegetation fires ranging from a minimum of 3.1% in 2003 to a maximum of 4.4% in 2001. Hot bare soils and gas flares were the major sources of false alarms and non-vegetation fires. The data were aggregated at 0.5° resolution for the global and local spatial autocorrelation Fire counts were found to be positively correlated up to distances of around 200 km, and negatively for larger distances. A value of 0.80 (p = 0.001, α = 0.05) for Moran's I indicates strong spatial autocorrelation between fires at global scale, with 60% of all cells displaying significant positive or negative spatial correlation. Different types of spatial autocorrelation were mapped and regression diagnostics allowed for the identification of spatial outlier cells, with fire counts much higher or lower than expected, considering their spatial context.
Landscape capability predicts upland game bird abundance and occurrence
Loman, Zachary G.; Blomberg, Erik J.; DeLuca, William; Harrison, Daniel J.; Loftin, Cyndy; Wood, Petra B.
2017-01-01
Landscape capability (LC) models are a spatial tool with potential applications in conservation planning. We used survey data to validate LC models as predictors of occurrence and abundance at broad and fine scales for American woodcock (Scolopax minor) and ruffed grouse (Bonasa umbellus). Landscape capability models were reliable predictors of occurrence but were less indicative of relative abundance at route (11.5–14.6 km) and point scales (0.5–1 km). As predictors of occurrence, LC models had high sensitivity (0.71–0.93) and were accurate (0.71–0.88) and precise (0.88 and 0.92 for woodcock and grouse, respectively). Models did not predict point-scale abundance independent of the ability to predict occurrence of either species. The LC models are useful predictors of patterns of occurrences in the northeastern United States, but they have limited utility as predictors of fine-scale or route-specific abundances.
Crustal evolution inferred from Apollo magnetic measurements
NASA Technical Reports Server (NTRS)
Dyal, P.; Daily, W. D.; Vanyan, L. L.
1978-01-01
Magnetic field and solar wind plasma density measurements were analyzed to determine the scale size characteristics of remanent fields at the Apollo 12, 15, and 16 landing sites. Theoretical model calculations of the field-plasma interaction, involving diffusion of the remanent field into the solar plasma, were compared to the data. The information provided by all these experiments shows that remanent fields over most of the lunar surface are characterized by spatial variations as small as a few kilometers. Large regions (50 to 100 km) of the lunar crust were probably uniformly magnetized during early crustal evolution. Bombardment and subsequent gardening of the upper layers of these magnetized regions left randomly oriented, smaller scale (5 to 10 km) magnetic sources close to the surface. The larger scale size fields of magnitude approximately 0.1 gammas are measured by the orbiting subsatellite experiments and the small scale sized remanent fields of magnitude approximately 100 gammas are measured by the surface experiments.
NASA Astrophysics Data System (ADS)
Adegoke, J. O.; Engelbrecht, F.; Vezhapparambu, S.
2013-12-01
In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.
NASA Astrophysics Data System (ADS)
Zarnetske, J. P.; Abbott, B. W.; Bowden, W. B.; Iannucci, F.; Griffin, N.; Parker, S.; Pinay, G.; Aanderud, Z.
2017-12-01
Dissolved organic carbon (DOC), nutrients, and other solute concentrations are increasing in rivers across the Arctic. Two hypotheses have been proposed to explain these trends: 1. distributed, top-down permafrost degradation, and 2. discrete, point-source delivery of DOC and nutrients from permafrost collapse features (thermokarst). While long-term monitoring at a single station cannot discriminate between these mechanisms, synoptic sampling of multiple points in the stream network could reveal the spatial structure of solute sources. In this context, we sampled carbon and nutrient chemistry three times over two years in 119 subcatchments of three distinct Arctic catchments (North Slope, Alaska). Subcatchments ranged from 0.1 to 80 km2, and included three distinct types of Arctic landscapes - mountainous, tundra, and glacial-lake catchments. We quantified the stability of spatial patterns in synoptic water chemistry and analyzed high-frequency time series from the catchment outlets across the thaw season to identify source areas for DOC, nutrients, and major ions. We found that variance in solute concentrations between subcatchments collapsed at spatial scales between 1 to 20 km2, indicating a continuum of diffuse- and point-source dynamics, depending on solute and catchment characteristics (e.g. reactivity, topography, vegetation, surficial geology). Spatially-distributed mass balance revealed conservative transport of DOC and nitrogen, and indicates there may be strong in-stream retention of phosphorus, providing a network-scale confirmation of previous reach-scale studies in these Arctic catchments. Overall, we present new approaches to analyzing synoptic data for change detection and quantification of ecohydrological mechanisms in ecosystems in the Arctic and beyond.
Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005-2015
NASA Astrophysics Data System (ADS)
Thompson, David R.; Kahn, Brian H.; Green, Robert O.; Chien, Steve A.; Middleton, Elizabeth M.; Tran, Daniel Q.
2018-02-01
The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.
Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula
NASA Astrophysics Data System (ADS)
Cho, H.; Choi, M.
2013-12-01
Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.
Bencala, K.E.; Gooseff, M.N.; Kimball, B.A.
2011-01-01
Although surface water and groundwater are increasingly referred to as one resource, there remain environmental and ecosystem needs to study the 10 m to 1 km reach scale as one hydrologic system. Streams gain and lose water over a range of spatial and temporal scales. Large spatial scales (kilometers) have traditionally been recognized and studied as river-aquifer connections. Over the last 25 years hyporheic exchange flows (1-10 m) have been studied extensively. Often a transient storage model has been used to quantify the physical solute transport setting in which biogeochemical processes occur. At the longer 10 m to 1 km scale of stream reaches it is now clear that streams which gain water overall can coincidentally lose water to the subsurface. At this scale, the amounts of water transferred are not necessarily significant but the exchanges can, however, influence solute transport. The interpretation of seemingly straightforward questions about water, contaminant, and nutrient fluxes into and along a stream can be confounded by flow losses which are too small to be apparent in stream gauging and along flow paths too long to be detected in tracer experiments. We suggest basic hydrologic approaches, e.g., measurement of flow along the channel, surface and subsurface solute sampling, and routine measurements of the water table that, in our opinion, can be used to extend simple exchange concepts from the hyporheic exchange scale to a scale of stream-catchment connection. Copyright 2011 by the American Geophysical Union.
Vulnerability of ecosystems to climate change moderated by habitat intactness.
Eigenbrod, Felix; Gonzalez, Patrick; Dash, Jadunandan; Steyl, Ilse
2015-01-01
The combined effects of climate change and habitat loss represent a major threat to species and ecosystems around the world. Here, we analyse the vulnerability of ecosystems to climate change based on current levels of habitat intactness and vulnerability to biome shifts, using multiple measures of habitat intactness at two spatial scales. We show that the global extent of refugia depends highly on the definition of habitat intactness and spatial scale of the analysis of intactness. Globally, 28% of terrestrial vegetated area can be considered refugia if all natural vegetated land cover is considered. This, however, drops to 17% if only areas that are at least 50% wilderness at a scale of 48×48 km are considered and to 10% if only areas that are at least 50% wilderness at a scale of 4.8×4.8 km are considered. Our results suggest that, in regions where relatively large, intact wilderness areas remain (e.g. Africa, Australia, boreal regions, South America), conservation of the remaining large-scale refugia is the priority. In human-dominated landscapes, (e.g. most of Europe, much of North America and Southeast Asia), focusing on finer scale refugia is a priority because large-scale wilderness refugia simply no longer exist. Action to conserve such refugia is particularly urgent since only 1 to 2% of global terrestrial vegetated area is classified as refugia and at least 50% covered by the global protected area network. © 2014 John Wiley & Sons Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wolfram, Phillip J.; Ringler, Todd D.; Maltrud, Mathew E.
Isopycnal diffusivity due to stirring by mesoscale eddies in an idealized, wind-forced, eddying, midlatitude ocean basin is computed using Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT). Simulation is performed via LIGHT within the Model for Prediction across Scales Ocean (MPAS-O). Simulations are performed at 4-, 8-, 16-, and 32-km resolution, where the first Rossby radius of deformation (RRD) is approximately 30 km. Scalar and tensor diffusivities are estimated at each resolution based on 30 ensemble members using particle cluster statistics. Each ensemble member is composed of 303 665 particles distributed across five potential density surfaces. Diffusivity dependence upon modelmore » resolution, velocity spatial scale, and buoyancy surface is quantified and compared with mixing length theory. The spatial structure of diffusivity ranges over approximately two orders of magnitude with values of O(10 5) m 2 s –1 in the region of western boundary current separation to O(10 3) m 2 s –1 in the eastern region of the basin. Dominant mixing occurs at scales twice the size of the first RRD. Model resolution at scales finer than the RRD is necessary to obtain sufficient model fidelity at scales between one and four RRD to accurately represent mixing. Mixing length scaling with eddy kinetic energy and the Lagrangian time scale yield mixing efficiencies that typically range between 0.4 and 0.8. In conclusion, a reduced mixing length in the eastern region of the domain relative to the west suggests there are different mixing regimes outside the baroclinic jet region.« less
NASA Astrophysics Data System (ADS)
Gao, Yang; Leung, L. Ruby; Zhao, Chun; Hagos, Samson
2017-03-01
Simulating summer precipitation is a significant challenge for climate models that rely on cumulus parameterizations to represent moist convection processes. Motivated by recent advances in computing that support very high-resolution modeling, this study aims to systematically evaluate the effects of model resolution and convective parameterizations across the gray zone resolutions. Simulations using the Weather Research and Forecasting model were conducted at grid spacings of 36 km, 12 km, and 4 km for two summers over the conterminous U.S. The convection-permitting simulations at 4 km grid spacing are most skillful in reproducing the observed precipitation spatial distributions and diurnal variability. Notable differences are found between simulations with the traditional Kain-Fritsch (KF) and the scale-aware Grell-Freitas (GF) convection schemes, with the latter more skillful in capturing the nocturnal timing in the Great Plains and North American monsoon regions. The GF scheme also simulates a smoother transition from convective to large-scale precipitation as resolution increases, resulting in reduced sensitivity to model resolution compared to the KF scheme. Nonhydrostatic dynamics has a positive impact on precipitation over complex terrain even at 12 km and 36 km grid spacings. With nudging of the winds toward observations, we show that the conspicuous warm biases in the Southern Great Plains are related to precipitation biases induced by large-scale circulation biases, which are insensitive to model resolution. Overall, notable improvements in simulating summer rainfall and its diurnal variability through convection-permitting modeling and scale-aware parameterizations suggest promising venues for improving climate simulations of water cycle processes.
Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions
NASA Astrophysics Data System (ADS)
Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.
2010-12-01
Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.
Fritts, Andrea; Knights, Brent C.; Lafrancois, Toben D.; Bartsch, Lynn; Vallazza, Jon; Bartsch, Michelle; Richardson, William B.; Karns, Byron N.; Bailey, Sean; Kreiling, Rebecca
2018-01-01
Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.
Understanding thermal circulations and near-surface turbulence processes in a small mountain valley
NASA Astrophysics Data System (ADS)
Pardyjak, E.; Dupuy, F.; Durand, P.; Gunawardena, N.; Thierry, H.; Roubin, P.
2017-12-01
The interaction of turbulence and thermal circulations in complex terrain can be significantly different from idealized flat terrain. In particular, near-surface horizontal spatial and temporal variability of winds and thermodynamic variables can be significant event over very small spatial scales. The KASCADE (KAtabatic winds and Stability over CAdarache for Dispersion of Effluents) 2017 conducted from January through March 2017 was designed to address these issues and to ultimately improve prediction of dispersion in complex terrain, particularly during stable atmospheric conditions. We have used a relatively large number of sensors to improve our understanding of the spatial and temporal development, evolution and breakdown of topographically driven flows. KASCADE 2017 consisted of continuous observations and fourteen Intensive Observation Periods (IOPs) conducted in the Cadarache Valley located in southeastern France. The Cadarache Valley is a relatively small valley (5 km x 1 km) with modest slopes and relatively small elevation differences between the valley floor and nearby hilltops ( 100 m). During winter, winds in the valley are light and stably stratified at night leading to thermal circulations as well as complex near-surface atmospheric layering. In this presentation we present results quantifying spatial variability of thermodynamic and turbulence variables as a function of different large -scale forcing conditions (e.g., quiescent conditions, strong westerly flow, and Mistral flow). In addition, we attempt to characterize highly-regular nocturnal horizontal wind meandering and associated turbulence statistics.
Savini, Alessandra; Vertino, Agostina; Marchese, Fabio; Beuck, Lydia; Freiwald, André
2014-01-01
In this study, we mapped the distribution of Cold-Water Coral (CWC) habitats on the northern Ionian Margin (Mediterranean Sea), with an emphasis on assessing coral coverage at various spatial scales over an area of 2,000 km(2) between 120 and 1,400 m of water depth. Our work made use of a set of data obtained from ship-based research surveys. Multi-scale seafloor mapping data, video inspections, and previous results from sediment samples were integrated and analyzed using Geographic Information System (GIS)-based tools. Results obtained from the application of spatial and textural analytical techniques to acoustic meso-scale maps (i.e. a Digital Terrain Model (DTM) of the seafloor at a 40 m grid cell size and associated terrain parameters) and large-scale maps (i.e. Side-Scan Sonar (SSS) mosaics of 1 m in resolution ground-truthed using underwater video observations) were integrated and revealed that, at the meso-scale level, the main morphological pattern (i.e. the aggregation of mound-like features) associated with CWC habitat occurrences was widespread over a total area of 600 km(2). Single coral mounds were isolated from the DTM and represented the geomorphic proxies used to model coral distributions within the investigated area. Coral mounds spanned a total area of 68 km(2) where different coral facies (characterized using video analyses and mapped on SSS mosaics) represent the dominant macro-habitat. We also mapped and classified anthropogenic threats that were identifiable within the examined videos, and, here, discuss their relationship to the mapped distribution of coral habitats and mounds. The combined results (from multi-scale habitat mapping and observations of the distribution of anthropogenic threats) provide the first quantitative assessment of CWC coverage for a Mediterranean province and document the relevant role of seafloor geomorphology in influencing habitat vulnerability to different types of human pressures.
Assessing and correcting spatial representativeness of tower eddy-covariance flux measurements
NASA Astrophysics Data System (ADS)
Metzger, S.; Xu, K.; Desai, A. R.; Taylor, J. R.; Kljun, N.; Blanken, P.; Burns, S. P.; Scott, R. L.
2014-12-01
Estimating the landscape-scale exchange of ecologically relevant trace gas and energy fluxes from tower eddy-covariance (EC) measurements is often complicated by surface heterogeneity. For example, a tower EC measurement may represent less than 1% of a grid cell resolved by mechanistic models (order 100-1000 km2). In particular for data assimilation or comparison with large-scale observations, it is hence critical to assess and correct the spatial representativeness of tower EC measurements. We present a procedure that determines from a single EC tower the spatio-temporally explicit flux field of its surrounding. The underlying principle is to extract the relationship between biophysical drivers and ecological responses from measurements under varying environmental conditions. For this purpose, high-frequency EC flux processing and source area calculations (≈60 h-1) are combined with remote sensing retrievals of land surface properties and subsequent machine learning. Methodological details are provided in our companion presentation "Towards the spatial rectification of tower-based eddy-covariance flux observations". We apply the procedure to one year of data from each of four AmeriFlux sites under different climate and ecological environments: Lost Creek shrub fen wetland, Niwot Ridge subalpine conifer, Park Falls mixed forest, and Santa Rita mesquite savanna. We find that heat fluxes from the Park Falls 122-m-high EC measurement and from a surrounding 100 km2 target area differ up to 100 W m-2, or 65%. Moreover, 85% and 24% of the EC flux observations are adequate surrogates of the mean surface-atmosphere exchange and its spatial variability across a 900 km2 target area, respectively, at 5% significance and 80% representativeness levels. Alternatively, the resulting flux grids can be summarized as probability density functions, and used to inform mechanistic models directly with the mean flux value and its spatial variability across a model grid cell. Lastly, for each site we evaluate the applicability of the procedure based on a full bottom-up uncertainty budget.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shrestha, Roshan; Houser, Paul R.; Anantharaj, Valentine G.
2011-04-01
Precipitation products are currently available from various sources at higher spatial and temporal resolution than any time in the past. Each of the precipitation products has its strengths and weaknesses in availability, accuracy, resolution, retrieval techniques and quality control. By merging the precipitation data obtained from multiple sources, one can improve its information content by minimizing these issues. However, precipitation data merging poses challenges of scale-mismatch, and accurate error and bias assessment. In this paper we present Optimal Merging of Precipitation (OMP), a new method to merge precipitation data from multiple sources that are of different spatial and temporal resolutionsmore » and accuracies. This method is a combination of scale conversion and merging weight optimization, involving performance-tracing based on Bayesian statistics and trend-analysis, which yields merging weights for each precipitation data source. The weights are optimized at multiple scales to facilitate multiscale merging and better precipitation downscaling. Precipitation data used in the experiment include products from the 12-km resolution North American Land Data Assimilation (NLDAS) system, the 8-km resolution CMORPH and the 4-km resolution National Stage-IV QPE. The test cases demonstrate that the OMP method is capable of identifying a better data source and allocating a higher priority for them in the merging procedure, dynamically over the region and time period. This method is also effective in filtering out poor quality data introduced into the merging process.« less
NASA Technical Reports Server (NTRS)
Mozer, F. S.; Agapitov, O. A.; Artemyev, A.; Burch, J. L.; Ergun, R. E.; Giles, B. L.; Mourenas, D.; Torbert, R. B.; Phan, T. D.; Vasko, I.
2016-01-01
The same time domain structures (TDS) have been observed on two Magnetospheric Multiscale Satellites near Earth's dayside magnetopause. These TDS, traveling away from the X line along the magnetic field at 4000 km/s, accelerated field-aligned approx. 5 eV electrons to approx. 200 eV by a single Fermi reflection of the electrons by these overtaking barriers. Additionally, the TDS contained both positive and negative potentials, so they were a mixture of electron holes and double layers. They evolve in approx.10 km of space or 7 ms of time and their spatial scale size is 10-20 km, which is much larger than the electron gyroradius (less than1km) or the electron inertial length (4 km at the observation point, less nearer the X line).
Global climate models (GCMs) are currently used to obtain information about future changes in the large-scale climate. However, such simulations are typically done at coarse spatial resolutions, with model grid boxes on the order of 100 km on a horizontal side. Therefore, techniq...
Hydrologic Landscape Regionalisation Using Deductive Classification and Random Forests
Brown, Stuart C.; Lester, Rebecca E.; Versace, Vincent L.; Fawcett, Jonathon; Laurenson, Laurie
2014-01-01
Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents. PMID:25396410
Hydrologic landscape regionalisation using deductive classification and random forests.
Brown, Stuart C; Lester, Rebecca E; Versace, Vincent L; Fawcett, Jonathon; Laurenson, Laurie
2014-01-01
Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.
Decorrelation scales for Arctic Ocean hydrography - Part I: Amerasian Basin
NASA Astrophysics Data System (ADS)
Sumata, Hiroshi; Kauker, Frank; Karcher, Michael; Rabe, Benjamin; Timmermans, Mary-Louise; Behrendt, Axel; Gerdes, Rüdiger; Schauer, Ursula; Shimada, Koji; Cho, Kyoung-Ho; Kikuchi, Takashi
2018-03-01
Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Amerasian Basin of the Arctic Ocean. For this purpose, we compile historical measurements from 1980 to 2015. Assuming spatial and temporal homogeneity of the decorrelation scale in the basin interior (abyssal plain area), we calculate autocorrelations as a function of spatial distance and temporal lag. The examination of the functional form of autocorrelation in each depth range reveals that the autocorrelation is well described by a Gaussian function in space and time. We derive decorrelation scales of 150-200 km in space and 100-300 days in time. These scales are directly applicable to quantify the representation error, which is essential for use of ocean in situ measurements in data assimilation. We also describe how the estimated autocorrelation function and decorrelation scale should be applied for cost function calculation in a data assimilation system.
Soil organic carbon - a large scale paired catchment assessment
NASA Astrophysics Data System (ADS)
Kunkel, V.; Hancock, G. R.; Wells, T.
2016-12-01
Soil organic carbon (SOC) concentration can vary both spatially and temporally driven by differences in soil properties, topography and climate. However most studies have focused on point scale data sets with a paucity of studies examining larger scale catchments. Here we examine the spatial and temporal distribution of SOC for two large catchments. The Krui (575 km2) and Merriwa River (675km2) catchments (New South Wales, Australia). Both have similar shape, soils, topography and orientation. We show that SOC distribution is very similar for both catchments and that elevation (and associated increase in soil moisture) is a major influence on SOC. We also show that there is little change in SOC from the initial assessment in 2006 to 2015 despite a major drought from 2003 to 2010 and extreme rainfall events in 2007 and 2010 -therefore SOC concentration appears robust. However, we found significant relationships between erosion and deposition patterns (as quantified using 137Cs) and SOC for both catchments again demonstrating a strong geomorphic relationship. Vegetation across the catchments was assessed using remote sensing (Landsat and MODIS). Vegetation patterns were temporally consistent with above ground biomass increasing with elevation. SOC could be predicted using both these low and high resolution remote sensing platforms. Results indicate that, although moderate resolution (250 m) allows for reasonable prediction of the spatial distribution of SOC, the higher resolution (30 m) improved the strength of the SOC-NDVI relationship. The relationship between SOC and 137Cs, as a surrogate for the erosion and deposition of SOC, suggested that sediment transport and deposition influences the distribution of SOC within the catchment. The findings demonstrate that over the large catchment scale and at the decadal time scale that SOC is relatively constant and can largely be predicted by topography.
Very high resolution observations of waves in the OH airglow at low latitudes.
NASA Astrophysics Data System (ADS)
Franzen, Christoph; Espy, Patrick J.; Hibbins, Robert E.; Djupvik, Amanda A.
2017-04-01
Vibrationally excited hydroxyl (OH) is produced in the mesosphere by the reaction of atomic hydrogen and ozone. This excited OH radiates a strong, near-infrared airglow emission in a thin ( 8 km thick) layer near 87 km. In the past, remote sensing of perturbations in the OH Meinel airglow has often been used to observe gravity, tidal and planetary waves travelling through this region. However, information on the highest frequency gravity waves is often limited by the temporal and spatial resolution of the available observations. In an effort to expand the wave scales present near the mesopause, we present a series of observations of the OH Meinel (9,7) transition that were executed with the Nordic Optical Telescope on La Palma (18°W, 29°N). These measurements are taken with a 10 s integration time (24 s repetition rate), and the spatial resolution at 87 km is as small as 10 m, allowing us to quantify the transition between the gravity and acoustic wave domains in the mesosphere.
Downscaling Coarse Actual ET Data Using Land Surface Resistance
NASA Astrophysics Data System (ADS)
Shen, T.
2017-12-01
This study proposed a new approach of downscaling ETWATCH 1km actual evapotranspiration (ET) product to a spatial resolution of 30m using land surface resistance that simulated mainly from monthly Landsat8 data and Jarvis method, which combined the benefits of both high temporal resolution of ETWATCH product and fine spatial resolution of Landsat8. The driving factor, surface resistance (Rs), was chosen for the reason that could reflect the transfer ability of vapor flow over canopy. Combined resistance Rs both upon canopy conditions, atmospheric factors and available water content of soil, which remains stable inside one ETWATCH pixel (1km). In this research, we used ETWATCH 1km ten-day actual ET product from April to October in a total of twenty-one images and monthly 30 meters cloud-free NDVI of 2013 (two images from HJ as a substitute due to cloud contamination) combined meteorological indicators for downscaling. A good agreement and correlation were obtained between the downscaled data and three flux sites observation in the middle reach of Heihe basin. The downscaling results show good consistency with the original ETWATCH 1km data both temporal and spatial scale over different land cover types with R2 ranged from 0.8 to 0.98. Besides, downscaled result captured the progression of vegetation transpiration well. This study proved the practicability of new downscaling method in the water resource management.
Representativeness of regional and global mass-balance measurement networks (Invited)
NASA Astrophysics Data System (ADS)
Cogley, J. G.; Moholdt, G.; Gardner, A. S.
2013-12-01
We showed in a recent publication that regional estimates of glacier mass budgets, obtained by interpolation from in-situ measurements, were markedly more negative than corresponding estimates by satellite gravimetry (GRACE) and satellite altimetry (ICESat) during 2003-2009. Examining the ICESat data in more detail, we found that in-situ records tend to be located in areas where glaciers are thinning more rapidly than as observed in their regional surroundings. Because neither GRACE nor ICESat can provide information for times before 2002-2003, and may not operate without interruption in the future, we explore possible explanations of and remedies for the identified bias in the in-situ network. Sparse spatial sampling, coupled with previously undetected spatial variability of mass balance at scales between the 10-km in-situ scale and the 350-km gravimetric scale, appears to be the leading explanation. Satisfactory remedies are not obvious. Selecting glaciers for in-situ measurement that are more representative will yield only incremental improvements. There appears to be no alternative to mass-balance modelling as a versatile tool for estimation of regional mass balance. However the meteorological data for forcing the surface components of glacier models have coarser resolution than is desirable and are themselves uncertain, especially in the remote regions where much of the glacier ice is found. Measurements of frontal (dynamic) mass changes are still difficult, and modelling of these changes remains underdeveloped in spite of recent advances. Thus research on a broad scale is called for in order to meet the challenge of producing more accurate hindcasts and projections of glacier mass budgets with fine spatial and temporal resolution.
Are big basins just the sum of small catchments?
Shaman, J.; Stieglitz, M.; Burns, D.
2004-01-01
Many challenges remain in extending our understanding of how hydrologic processes within small catchments scale to larger river basins. In this study we examine how low-flow runoff varies as a function of basin scale at 11 catchments, many of which are nested, in the 176 km2 Neversink River watershed in the Catskill Mountains of New York. Topography, vegetation, soil and bedrock structure are similar across this river basin, and previous research has demonstrated the importance of deep groundwater springs for maintaining low-flow stream discharge at small scales in the basin. Therefore, we hypothesized that deep groundwater would contribute an increasing amount to low-flow discharge as basin scale increased, resulting in increased runoff. Instead, we find that, above a critical basin size of 8 to 21 km2, low-flow runoff is similar within the Neversink watershed. These findings are broadly consistent with those of a previous study that examined stream chemistry as a function of basin scale for this watershed. However, we find physical evidence of self-similarity among basins greater than 8 km2, whereas the previous study found gradual changes in stream chemistry among basins greater than 3 km 2. We believe that a better understanding of self-similarity and the subsurface flow processes that affect stream runoff will be attained through simultaneous consideration of both chemical and physical evidence. We also suggest that similar analyses of stream runoff in other basins that represent a range of spatial scales, geomorphologies and climate conditions will further elucidate the issue of scaling of hydrologic processes. Copyright ?? 2004 John Wiley & Sons, Ltd.
Pinard, F; Makune, S E; Campagne, P; Mwangi, J
2016-11-01
Based on time and spatial dynamic considerations, this study evaluates the potential role of short- and long-distance dispersal in the spread of coffee wilt disease (CWD) in a large commercial Robusta coffee estate in Uganda (Kaweri, 1,755 ha) over a 4-year period (2008 to 2012). In monthly surveys, total disease incidence, expansion of infection foci, and the occurrence of isolated infected trees were recorded and submitted to spatial analysis. Incidence was higher and disease progression faster in old coffee plantings compared with young plantings, indicating a lack of efficiency of roguing for reducing disease development in old plantings. At large spatial scale (approximately 1 km), Moran indices (both global and local) revealed the existence of clusters characterized by contrasting disease incidences. This suggested that local environmental conditions were heterogeneous or there were spatial interactions among blocks. At finer spatial scale (approximately 200 m), O-ring statistics revealed positive correlation between distant infection sites across distances as great as 60 m. Although these observations indicate the role of short-distance dispersal in foci expansion, dispersal at greater distances (>20 m) appeared to also contribute to both initiation of new foci and disease progression at coarser spatial scales. Therefore, our results suggested the role of aerial dispersal in CWD progression.
NASA Astrophysics Data System (ADS)
Sheridan, Gary; nyman, petter; Duff, Tom; Baillie, Craig; Bovill, William; Lane, Patrick; Tolhurst, Kevin
2015-04-01
The prediction of fuel moisture content is important for estimating the rate of spread of wildfires, the ignition probability of firebrands, and for the efficient scheduling of prescribed fire. The moisture content of fine surface fuels varies spatially at large scales (10's to 100's km) due to variation in meteorological variables (eg. temperature, relative humidity, precipitation). At smaller scales (100's of metres) in steep topography spatial variability is attributed to topographic influences that include differences in radiation due to aspect and slope, differences in precipitation, temperature and relative humidity due to elevation, and differences in soil moisture due to hillslope drainage position. Variable forest structure and canopy shading adds further to the spatial variability in surface fuel moisture. In this study we aim to combine daily 5km resolution gridded weather data with 20m resolution DEM and vegetation structure data to predict the spatial variability of fine surface fuels in steep topography. Microclimate stations were established in south east Australia to monitor surface fine fuel moisture continuously (every 15 minutes) using newly developed instrumented litter packs, in addition to temperature and relative humidity measurements inside the litter pack, and measurement of precipitation and energy inputs above and below the forest canopy. Microclimate stations were established across a gradient of aspect (5 stations), drainage position (7 stations), elevation (15 stations), and canopy cover conditions (6 stations). The data from this extensive network of microclimate stations across a broad spectrum of topographic conditions is being analysed to enable the downscaling of gridded weather data to spatial scales that are relevant to the connectivity of wildfire fuels and to the scheduling and outcome of prescribed fires. The initial results from the first year of this study are presented here.
Snow depth spatial structure from hillslope to basin scale
NASA Astrophysics Data System (ADS)
Deems, J. S.
2017-12-01
Knowledge of spatial patterns of snow accumulation is required for understanding the hydrology, climatology, and ecology of mountain regions. Spatial structure in snow accumulation patterns changes with the scale of observation, a feature that has been characterized using fractal dimensions calculated from lidar-derived snow depth maps: fractal scaling structure at short length scales, with a `scale break' transition to more stochastic patterns at longer separation distances. Previous work has shown that this fractal structure of snow depth distributions differs between sites with different vegetation and terrain characteristics. Forested areas showed a transition to a nearly random spatial distribution at a much shorter lag distance than do unforested sites, enabling a statistical characterization. Alpine areas, however, showed strong spatial structure for a much wider scale range, and were the source of the dominant spatial pattern observable over a wider area. These spatial structure characteristics suggest that the choice of measurement or model resolution (satellite sensor, DEM, field survey point spacing, etc.) will strongly affect the estimates of snow volume or mass, as well as the magnitude of spatial variability. These prior efforts used data sets that were high resolution ( 1 m laser point spacing) but of limited extent ( 1 km2), constraining detection of scale features such as fractal dimension or scale breaks to areas of relatively similar characteristics and to lag distances of under 500 m. New datasets available from the NASA JPL Airborne Snow Observatory (ASO) provide similar resolution but over large areas, enabling assessment of snow spatial structure across an entire watershed, or in similar vegetation or physiography but in different parts of the basin. Additionally, the multi-year ASO time series allows an investigation into the temporal stability of these scale characteristics, within a single snow season and between seasons of strongly varying accumulation totals and patterns. This presentation will explore initial results from this study, using data from the Tuolumne River Basin in California, USA. Fractal scaling characteristics derived from ASO lidar snow depth measurements are examined at the basin scale, as well as in varying topographic and forest cover environments.
Hassan, A N; Dister, S; Beck, L
1998-04-01
Geographic information system (GIS) was used to analyze the spatial distribution of filariasis in the Nile Delta. The study involved 201 villages belonging to Giza, Qalubiya, Monoufiya, Gharbiya, and Dakahliya governorates. Villages with similar microfilarial (mf) prevalence rates were observed to cluster within 1-2 km distance, then, clustering started to decrease significantly with distance up to 5 km (Pearson correlation coefficient = -0.98). the likelihood of negative and high prevalence villages being contiguous was very low (approximately 1.8%, n = 612 village-pairs) indicating homogeneity in disease processes within the defined spatial scales. Of the villages located within 2 km from the main Nile branches (n = 46), 95% exhibited low prevalence. In addition, the spatial pattern of mf prevalence was shown to be negatively associated with annual rainfall and relative humidity, while it was positively associated with annual daily temperature. Average mf prevalence in warmer, relatively drier areas receiving 25 mm of rain was significantly higher (3.9%) than that in less warmer but more humid areas receiving 50 mm of rain (1.6%) (P < 0.0001). Based on the results of the present study, GIS was used to generate a "filariasis risk map" that could be used by health authorities to efficiently direct surveillance and control efforts. This investigation identified some of the factors underlying filariasis spatial pattern, quantified clustering and demonstrated the potential of GIS application in vector-borne disease epidemiology.
DOE Office of Scientific and Technical Information (OSTI.GOV)
De Pontieu, B.; Martinez-Sykora, J.; McIntosh, S.
Spectral observations of the solar transition region (TR) and corona show broadening of spectral lines beyond what is expected from thermal and instrumental broadening. The remaining non-thermal broadening is significant (5–30 km s{sup −1}) and correlated with intensity. Here we study spectra of the TR Si iv 1403 Å line obtained at high resolution with the Interface Region Imaging Spectrograph (IRIS). We find that the large improvement in spatial resolution (0.″33) of IRIS compared to previous spectrographs (2″) does not resolve the non-thermal line broadening which, in most regions, remains at pre-IRIS levels of about 20 km s{sup −1}. Thismore » invariance to spatial resolution indicates that the processes behind the broadening occur along the line-of-sight (LOS) and/or on spatial scales (perpendicular to the LOS) smaller than 250 km. Both effects appear to play a role. Comparison with IRIS chromospheric observations shows that, in regions where the LOS is more parallel to the field, magneto-acoustic shocks driven from below impact the TR and can lead to significant non-thermal line broadening. This scenario is supported by MHD simulations. While these do not show enough non-thermal line broadening, they do reproduce the long-known puzzling correlation between non-thermal line broadening and intensity. This correlation is caused by the shocks, but only if non-equilibrium ionization is taken into account. In regions where the LOS is more perpendicular to the field, the prevalence of small-scale twist is likely to play a significant role in explaining the invariance and correlation with intensity. (letters)« less
Soil erosion rates (particulate and dissolved fluxes) variations in a temperate river basin
NASA Astrophysics Data System (ADS)
Cerdan, Olivier; Gay, Aurore; Négrel, Philippe; Pételet-Giraud, Emmanuelle; Salvador Blanes, Sébastien; Degan, Francesca
2015-04-01
Soil erosion is one of the major drivers of landscape evolution in Western Europe. However, depending on the land use characteristics and on the geological and topographical settings, miscellaneous forms of erosion may lead to a very diverse morphological evolution. To understand these landscape evolutions different scientific questions remain to be answered or quantified. The main difficulty arises from the nonlinear interactions between different erosional processes that act at different temporal and spatial scales. This study proposes to investigate different datasets describing particulate and dissolved sediment fluxes within a French River basin (The Loire River) at different spatial scales and at temporal scales ranging from the flood event to several decades. The particulate sediment load values at the outlet of the catchments range from 2.5 102 to 8.6 105 t yr-1, and the sediment yield values range from 2.9 to 32.4 t km 2 yr-1. Sediment exports from the Loire and Brittany river basins are low compared with mountainous regions and European exports. However, a strong spatial variability within this territory exists. The expected results on the sediment yield spatial pattern distribution and the correlation between SY values and basin sizes are not observed. An analysis of the sediment yield values at different time steps shows a strong effect of the seasonal availability of detached particles to be transported. High concentrations of suspended sediments during the winter and lower values during the summer and autumn are observed. Inter-annual variations are also observed, with export values varying by a factor 2 to 10 between years for one catchment. The influence of rainfall on the sediment exports is predominant, but investigations on physical characteristics of each catchment (e.g., lithology, slope, land use) are required to better understand the production and transfer processes within a drainage basin. These inter-annual variations imply that long-term data are required to provide mean SY values representative of the catchment functioning. From our calculations, 18 complete years of data are required to obtain a mean sediment yield value with less than 10% of variation on average around the mean. The specific dissolved fluxes vary from 13.7 to 199.9 t.km-2. t yr-1. Contrary to particulate matters, the impact of the lithology is illustrated by higher total dissolved solid fluxes on limestone catchments compared with graniteous or schisteous catchments. Nitrates and ammonium are indicators of anthropogenic perturbation and their fluxes vary respectively from 0.4 to 31.4 t.km-2. yr-1 and from 7.8*10-3 to 7.7 t.km-2. yr-1 and evolve differently according to land uses: nitrates fluxes are lower in the upstream Loire and higher downstream in the region where agricultural pressure is higher. The analysis of these datasets at different spatial and temporal scales permits to identify some of the dominant processes, and also to distinguish natural from anthropogenic influences. Concerning upland physical soil surface erosion rates, we find that the average travel distance of eroded particles may be limited, implying a strong decrease in physical erosion rates when moving from the local scale (m²) to the river basin scale (> 103 km²). Chemical erosion rates are less sensitive to scale and can either decrease or increase with increasing area in function of lithology, land management and topography. The results also highlight the predominant role of surface connectivity to characterize the fraction of sediment exported out of river drainage areas by physical soil surface erosion. For the export of dissolved sediment originating from weathering processes, the catchment physiography and connectivity does no longer play the dominant role. A direct link between soil production rates and exported dissolved fluxes tends to show that, contrary to the suspended particles, which are transport-limited, the dissolved matter seems to be supply-limited.
NASA Astrophysics Data System (ADS)
Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.
2017-12-01
Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.
NASA Astrophysics Data System (ADS)
Marra, Francesco; Morin, Efrat
2018-02-01
Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.
Expanding Scales and Applications for 2D Spatial Mapping of CO2 using GreenLITE
NASA Astrophysics Data System (ADS)
Erxleben, W. H.; Dobler, J. T.; Zaccheo, T. S.; Blume, N.; Braun, M.
2015-12-01
The Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE) system is a new measurement approach originally developed under a cooperative agreement with the Department of Energy (DOE) National Energy Technology Laboratory (NETL), Atmospheric Environmental Sciences (AER) and Exelis Inc. (now part of Harris Corp.). The original system design provides 24/7 monitoring of Ground Carbon Storage (GCS) sites, in order to help ensure worker safety and verify 99% containment. The first generation was designed to cover up to 1km2 area, and employs the Exelis Continuous Wave (CW) Intensity Modulated (IM) approach to measure differential transmission. A pair of scanning transceivers was built and combined with a series of retro reflectors, and a local weather station to provide the information required for producing estimates of the atmospheric CO2 concentration over a number of overlapping lines-of-site. The information from the transceivers, and weather station, are sent remotely to a web-based processing and storage tool, which in-turn uses the data to generate estimates of the 2D spatial distribution over the area of coverage and disseminate that information near real-time via a secure web interface. Recently, in 2015, Exelis and AER have invested in the expansion of the GreenLITE transceiver system to 5 km range, enabling areas up to 25 km2 to be evaluated with this technology, and opening new possibilities for applications such as urban scale monitoring. The 5 km system is being tested in conjunction with the National Institute of Standards and Technology at the Boulder Atmospheric Observatory in August of this year. This talk will review the initial GreenLITE system, testing and deployment of that system, and the more recent development, expansion and testing of the 5 km system.
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.
Wong, A Y; Chen, J; Lee, L C; Liu, L Y
2009-03-13
A large density cavity that measured 2000 km across and 500 km in height was observed by DEMETER and Formosat/COSMIC satellites in temporal and spatial relation to a new mode of propagation of electromagnetic (em) pulses between discrete magnetic field-aligned auroral plasmas to high altitudes. Recorded positive plasma potential from satellite probes is consistent with the expulsion of electrons in the creation of density cavities. High-frequency decay spectra support the concept of parametric instabilities fed by free energy sources.
NASA Astrophysics Data System (ADS)
Peng, Dailiang; Zhang, Xiaoyang; Zhang, Bing; Liu, Liangyun; Liu, Xinjie; Huete, Alfredo R.; Huang, Wenjiang; Wang, Siyuan; Luo, Shezhou; Zhang, Xiao; Zhang, Helin
2017-10-01
Land surface phenology (LSP) has been widely retrieved from satellite data at multiple spatial resolutions, but the spatial scaling effects on LSP detection are poorly understood. In this study, we collected enhanced vegetation index (EVI, 250 m) from collection 6 MOD13Q1 product over the contiguous United States (CONUS) in 2007 and 2008, and generated a set of multiple spatial resolution EVI data by resampling 250 m to 2 × 250 m and 3 × 250 m, 4 × 250 m, …, 35 × 250 m. These EVI time series were then used to detect the start of spring season (SOS) at various spatial resolutions. Further the SOS variation across scales was examined at each coarse resolution grid (35 × 250 m ≈ 8 km, refer to as reference grid) and ecoregion. Finally, the SOS scaling effects were associated with landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation within each reference grid. The results revealed the influences of satellite spatial resolutions on SOS retrievals and the related impact factors. Specifically, SOS significantly varied lineally or logarithmically across scales although the relationship could be either positive or negative. The overall SOS values averaged from spatial resolutions between 250 m and 35 × 250 m at large ecosystem regions were generally similar with a difference less than 5 days, while the SOS values within the reference grid could differ greatly in some local areas. Moreover, the standard deviation of SOS across scales in the reference grid was less than 5 days in more than 70% of area over the CONUS, which was smaller in northeastern than in southern and western regions. The SOS scaling effect was significantly associated with heterogeneity of vegetation properties characterized using land landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation, but the latter was the most important impact factor.
Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions
Feng, Sha; Lauvaux, Thomas; Newman, Sally; ...
2016-07-22
Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less
Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO 2 emissions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Feng, Sha; Lauvaux, Thomas; Newman, Sally
Megacities are major sources of anthropogenic fossil fuel CO 2 (FFCO 2) emissions. The spatial extents of these large urban systems cover areas of 10 000 km 2 or more with complex topography and changing landscapes. We present a high-resolution land–atmosphere modelling system for urban CO 2 emissions over the Los Angeles (LA) megacity area. The Weather Research and Forecasting (WRF)-Chem model was coupled to a very high-resolution FFCO 2 emission product, Hestia-LA, to simulate atmospheric CO 2 concentrations across the LA megacity at spatial resolutions as fine as ~1 km. We evaluated multiple WRF configurations, selecting one that minimizedmore » errors in wind speed, wind direction, and boundary layer height as evaluated by its performance against meteorological data collected during the CalNex-LA campaign (May–June 2010). Our results show no significant difference between moderate-resolution (4 km) and high-resolution (1.3 km) simulations when evaluated against surface meteorological data, but the high-resolution configurations better resolved planetary boundary layer heights and vertical gradients in the horizontal mean winds. We coupled our WRF configuration with the Vulcan 2.2 (10 km resolution) and Hestia-LA (1.3 km resolution) fossil fuel CO 2 emission products to evaluate the impact of the spatial resolution of the CO 2 emission products and the meteorological transport model on the representation of spatiotemporal variability in simulated atmospheric CO 2 concentrations. We find that high spatial resolution in the fossil fuel CO 2 emissions is more important than in the atmospheric model to capture CO 2 concentration variability across the LA megacity. Finally, we present a novel approach that employs simultaneous correlations of the simulated atmospheric CO 2 fields to qualitatively evaluate the greenhouse gas measurement network over the LA megacity. Spatial correlations in the atmospheric CO 2 fields reflect the coverage of individual measurement sites when a statistically significant number of sites observe emissions from a specific source or location. We conclude that elevated atmospheric CO 2 concentrations over the LA megacity are composed of multiple fine-scale plumes rather than a single homogenous urban dome. Furthermore, we conclude that FFCO 2 emissions monitoring in the LA megacity requires FFCO 2 emissions modelling with ~1 km resolution because coarser-resolution emissions modelling tends to overestimate the observational constraints on the emissions estimates.« less
Bright points and ejections observed on the sun by the KORONAS-FOTON instrument TESIS
NASA Astrophysics Data System (ADS)
Ulyanov, A. S.; Bogachev, S. A.; Kuzin, S. V.
2010-10-01
Five-second observations of the solar corona carried out in the FeIX 171 Å line by the KORONAS-FOTON instrument TESIS are used to study the dynamics of small-scale coronal structures emitting in and around coronal bright points. The small-scale structures of the lower corona display complex dynamics similar to those of magnetic loops located at higher levels of the solar corona. Numerous detected oscillating structures with sizes below 10 000 km display oscillation periods from 50 to 350 s. The period distributions of these structures are different for P < 150 s and P > 150 s, which implies that different oscillation modes are excited at different periods. The small-scale structures generate numerous flare-like events with energies 1024-1026 erg (nanoflares) and with a spatial density of one event per arcsecond or more observed over an area of 4 × 1011 km2. Nanoflares are not associated with coronal bright points, and almost uniformly cover the solar disk in the observation region. The ejections of solar material from the coronal bright points demonstrate velocities of 80-110 km/s.
Mesospheric plasma irregularities caused by the missile destruction on 9 December 2009
NASA Astrophysics Data System (ADS)
Kozlovsky, Alexander; Shalimov, Sergey; Lester, Mark
2017-06-01
On 9 December 2009 at about 07 UT a solid propellant 36.8 t ballistic rocket was self-destroyed at an altitude of 170-260 km, at a distance of about 500 km to the east of Sodankylä Geophysical Observatory (SGO, 67°22'N, 26°38'E, Finland). After 2-3 h the SGO meteor radar (operating at a frequency 36.9 MHz) received unusual echoes, which indicate turbulence of ionospheric plasma (irregularities of electron density) with a temporal scale on the order of 0.1 s and a spatial scale of a few to tens of meters. The turbulence occurred at a height of about 80 km and was localized in several areas of about 60 km in horizontal scale. Line-of-sight velocity of the irregularities was up to a few tens of meters per second toward the radar. The event occurred in the winter high-latitude mesosphere during extremely low solar and geomagnetic activity. Aerosol particles caused by the missile explosion played a key role in producing the electron density irregularities. As a possible explanation, we suggest that sedimented by gravity and, hence, moving with respect to the air, charged aerosol particles (presumably composed of aluminum oxide) might produce meter-scale irregularities (electrostatic waves) via dissipative instability, which is a mechanism analogous to that of the resistive beam-plasma instability.
NASA Astrophysics Data System (ADS)
Guihou, K.; Polton, J.; Harle, J.; Wakelin, S.; O'Dea, E.; Holt, J.
2018-01-01
The North West European Shelf break acts as a barrier to the transport and exchange between the open ocean and the shelf seas. The strong spatial variability of these exchange processes is hard to fully explore using observations, and simulations generally are too coarse to simulate the fine-scale processes over the whole region. In this context, under the FASTNEt program, a new NEMO configuration of the North West European Shelf and Atlantic Margin at 1/60° (˜1.8 km) has been developed, with the objective to better understand and quantify the seasonal and interannual variability of shelf break processes. The capability of this configuration to reproduce the seasonal cycle in SST, the barotropic tide, and fine-resolution temperature profiles is assessed against a basin-scale (1/12°, ˜9 km) configuration and a standard regional configuration (7 km resolution). The seasonal cycle is well reproduced in all configurations though the fine-resolution allows the simulation of smaller scale processes. Time series of temperature at various locations on the shelf show the presence of internal waves with a strong spatiotemporal variability. Spectral analysis of the internal waves reveals peaks at the diurnal, semidiurnal, inertial, and quarter-diurnal bands, which are only realistically reproduced in the new configuration. Tidally induced pycnocline variability is diagnosed in the model and shown to vary with the spring neap cycle with mean displacement amplitudes in excess of 2 m for 30% of the stratified domain. With sufficiently fine resolution, internal tides are shown to be generated at numerous bathymetric features resulting in a complex pycnocline displacement superposition pattern.
NASA Astrophysics Data System (ADS)
Hirt, Christian; Reußner, Elisabeth; Rexer, Moritz; Kuhn, Michael
2016-09-01
Over the past years, spectral techniques have become a standard to model Earth's global gravity field to 10 km scales, with the EGM2008 geopotential model being a prominent example. For some geophysical applications of EGM2008, particularly Bouguer gravity computation with spectral techniques, a topographic potential model of adequate resolution is required. However, current topographic potential models have not yet been successfully validated to degree 2160, and notable discrepancies between spectral modeling and Newtonian (numerical) integration well beyond the 10 mGal level have been reported. Here we accurately compute and validate gravity implied by a degree 2160 model of Earth's topographic masses. Our experiments are based on two key strategies, both of which require advanced computational resources. First, we construct a spectrally complete model of the gravity field which is generated by the degree 2160 Earth topography model. This involves expansion of the topographic potential to the 15th integer power of the topography and modeling of short-scale gravity signals to ultrahigh degree of 21,600, translating into unprecedented fine scales of 1 km. Second, we apply Newtonian integration in the space domain with high spatial resolution to reduce discretization errors. Our numerical study demonstrates excellent agreement (8 μGgal RMS) between gravity from both forward modeling techniques and provides insight into the convergence process associated with spectral modeling of gravity signals at very short scales (few km). As key conclusion, our work successfully validates the spectral domain forward modeling technique for degree 2160 topography and increases the confidence in new high-resolution global Bouguer gravity maps.
Singh, Minerva; Friess, Daniel A; Vilela, Bruno; Alban, Jose Don T De; Monzon, Angelica Kristina V; Veridiano, Rizza Karen A; Tumaneng, Roven D
2017-01-01
This study maps distribution and spatial congruence between Above-Ground Biomass (AGB) and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs) extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1). A support vector regression (SVR) model was used to identify the factors influencing variation in avian species richness at a 1km scale. AGB is one of the most important determinants of avian species richness for the study area. Topographic factors and anthropogenic factors such as distance from the roads were also found to strongly influence avian species richness. Hotspots of high AGB and high species richness concentration were mapped using hotspot analysis and the overlaps between areas of high AGB and avian species richness was calculated. Results show that the overlaps between areas of high AGB with high IUCN red listed avian species richness and endemic avian species richness were fairly limited at 13% and 8% at the 1-km scale. The overlap between 1) low AGB and low IUCN richness, and 2) low AGB and low endemic avian species richness was higher at 36% and 12% respectively. The enhanced capacity to spatially map the correlation between AGB and avian species richness distribution will further assist the conservation and protection of forest areas and threatened avian species.
NASA Astrophysics Data System (ADS)
van der Velde, Y.; Rozemeijer, J. C.; de Rooij, G. H.; van Geer, F. C.; Torfs, P. J. J. F.; de Louw, P. G. B.
2010-10-01
Identifying effective measures to reduce nutrient loads of headwaters in lowland catchments requires a thorough understanding of flow routes of water and nutrients. In this paper we assess the value of nested-scale discharge and groundwater level measurements for predictions of catchment-scale discharge and nitrate loads. In order to relate field-site measurements to the catchment-scale an upscaling approach is introduced that assumes that scale differences in flow route fluxes originate from differences in the relationship between groundwater storage and the spatial structure of the groundwater table. This relationship is characterized by the Groundwater Depth Distribution (GDD) curve that relates spatial variation in groundwater depths to the average groundwater depth. The GDD-curve was measured for a single field site (0.009 km2) and simple process descriptions were applied to relate the groundwater levels to flow route discharges. This parsimonious model could accurately describe observed storage, tube drain discharge, overland flow and groundwater flow simultaneously with Nash-Sutcliff coefficients exceeding 0.8. A probabilistic Monte Carlo approach was applied to upscale field-site measurements to catchment scales by inferring scale-specific GDD-curves from hydrographs of two nested catchments (0.4 and 6.5 km2). The estimated contribution of tube drain effluent (a dominant source for nitrates) decreased with increasing scale from 76-79% at the field-site to 34-61% and 25-50% for both catchment scales. These results were validated by demonstrating that a model conditioned on nested-scale measurements simulates better nitrate loads and better predictions of extreme discharges during validation periods compared to a model that was conditioned on catchment discharge only.
Predator-guided sampling reveals biotic structure in the bathypelagic.
Benoit-Bird, Kelly J; Southall, Brandon L; Moline, Mark A
2016-02-24
We targeted a habitat used differentially by deep-diving, air-breathing predators to empirically sample their prey's distributions off southern California. Fine-scale measurements of the spatial variability of potential prey animals from the surface to 1,200 m were obtained using conventional fisheries echosounders aboard a surface ship and uniquely integrated into a deep-diving autonomous vehicle. Significant spatial variability in the size, composition, total biomass, and spatial organization of biota was evident over all spatial scales examined and was consistent with the general distribution patterns of foraging Cuvier's beaked whales (Ziphius cavirostris) observed in separate studies. Striking differences found in prey characteristics between regions at depth, however, did not reflect differences observed in surface layers. These differences in deep pelagic structure horizontally and relative to surface structure, absent clear physical differences, change our long-held views of this habitat as uniform. The revelation that animals deep in the water column are so spatially heterogeneous at scales from 10 m to 50 km critically affects our understanding of the processes driving predator-prey interactions, energy transfer, biogeochemical cycling, and other ecological processes in the deep sea, and the connections between the productive surface mixed layer and the deep-water column. © 2016 The Author(s).
OpenMP parallelization of a gridded SWAT (SWATG)
NASA Astrophysics Data System (ADS)
Zhang, Ying; Hou, Jinliang; Cao, Yongpan; Gu, Juan; Huang, Chunlin
2017-12-01
Large-scale, long-term and high spatial resolution simulation is a common issue in environmental modeling. A Gridded Hydrologic Response Unit (HRU)-based Soil and Water Assessment Tool (SWATG) that integrates grid modeling scheme with different spatial representations also presents such problems. The time-consuming problem affects applications of very high resolution large-scale watershed modeling. The OpenMP (Open Multi-Processing) parallel application interface is integrated with SWATG (called SWATGP) to accelerate grid modeling based on the HRU level. Such parallel implementation takes better advantage of the computational power of a shared memory computer system. We conducted two experiments at multiple temporal and spatial scales of hydrological modeling using SWATG and SWATGP on a high-end server. At 500-m resolution, SWATGP was found to be up to nine times faster than SWATG in modeling over a roughly 2000 km2 watershed with 1 CPU and a 15 thread configuration. The study results demonstrate that parallel models save considerable time relative to traditional sequential simulation runs. Parallel computations of environmental models are beneficial for model applications, especially at large spatial and temporal scales and at high resolutions. The proposed SWATGP model is thus a promising tool for large-scale and high-resolution water resources research and management in addition to offering data fusion and model coupling ability.
Addressing Common Cloud-Radiation Errors from 4-hour to 4-week Model Prediction
NASA Astrophysics Data System (ADS)
Benjamin, S.; Sun, S.; Grell, G. A.; Green, B.; Olson, J.; Kenyon, J.; James, E.; Smirnova, T. G.; Brown, J. M.
2017-12-01
Cloud-radiation representation in models for subgrid-scale clouds is a known gap from subseasonal-to-seasonal models down to storm-scale models applied for forecast duration of only a few hours. NOAA/ESRL has been applying common physical parameterizations for scale-aware deep/shallow convection and boundary-layer mixing over this wide range of time and spatial scales, with some progress to be reported in this presentation. The Grell-Freitas scheme (2014, Atmos. Chem. Phys.) and MYNN boundary-layer EDMF scheme (Olson / Benjamin et al. 2016 Mon. Wea. Rev.) have been applied and tested extensively for the NOAA hourly updated 3-km High-Resolution Rapid Refresh (HRRR) and 13-km Rapid Refresh (RAP) model/assimilation systems over the United States and North America, with targeting toward improvement to boundary-layer evolution and cloud-radiation representation in all seasons. This representation is critical for both warm-season severe convective storm forecasting and for winter-storm prediction of snow and mixed precipitation. At the same time the Grell-Freitas scheme has been applied also as an option for subseasonal forecasting toward improved US week 3-4 prediction with the FIM-HYCOM coupled model (Green et al 2017, MWR). Cloud/radiation evaluation using CERES satellite-based estimates have been applied to both 12-h RAP (13km) and also during Weeks 1-4 from 32-day FIM-HYCOM (60km) forecasts. Initial results reveal that improved cloud representation is needed for both resolutions and now is guiding further refinement for cloud representation including with the Grell-Freitas scheme and with the updated MYNN-EDMF scheme (both now also in global testing as well as with the 3km HRRR and 13km RAP models).
Rousselet, Jérôme; Imbert, Charles-Edouard; Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre
2013-01-01
Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google Street View could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google Street View. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google Street View were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google Street View network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant.
NASA Astrophysics Data System (ADS)
Günther, Andreas; Van Den Eeckhaut, Miet; Malet, Jean-Philippe; Reichenbach, Paola; Hervás, Javier
2014-11-01
With the adoption of the EU Thematic Strategy for Soil Protection in 2006, small-scale (1:1 M) assessments of threats affecting soils over Europe received increasing attention. As landslides have been recognized as one of eight threats requiring a Pan-European evaluation, we present an approach for landslide susceptibility evaluation at the continental scale over Europe. Unlike previous continental and global scale landslide susceptibility studies not utilizing spatial information on the events, we collected more than 102,000 landslide locations in 22 European countries. These landslides are heterogeneously distributed over Europe, but are indispensable for the evaluation and classification of Pan-European datasets used as spatial predictors, and the validation of the resulting assessments. For the analysis we subdivided the European territory into seven different climate-physiographical zones by combining morphometric and climatic data for terrain differentiation, and adding a coastal zone defined as a 1 km strip inland from the coastline. Landslide susceptibility modeling was performed for each zone using heuristic spatial multicriteria evaluations supported by analytical hierarchy processes, and validated with the inventory data using the receiver operating characteristics. In contrast to purely data-driven statistical modeling techniques, our semi-quantitative approach is capable to introduce expert knowledge into the analysis, which is indispensable considering quality and resolution of the input data, and incompleteness and bias in the inventory information. The reliability of the resulting susceptibility map ELSUS 1000 Version 1 (1 km resolution) was examined on an administrative terrain unit level in areas with landslide information and through the comparison with available national susceptibility zonations. These evaluations suggest that although the ELSUS 1000 is capable for a correct synoptic prediction of landslide susceptibility in the majority of the area, it needs further improvement in terms of data used.
Dekri, Anissa; Garcia, Jacques; Goussard, Francis; Vincent, Bruno; Denux, Olivier; Robinet, Christelle; Dorkeld, Franck; Roques, Alain; Rossi, Jean-Pierre
2013-01-01
Mapping species spatial distribution using spatial inference and prediction requires a lot of data. Occurrence data are generally not easily available from the literature and are very time-consuming to collect in the field. For that reason, we designed a survey to explore to which extent large-scale databases such as Google maps and Google street view could be used to derive valid occurrence data. We worked with the Pine Processionary Moth (PPM) Thaumetopoea pityocampa because the larvae of that moth build silk nests that are easily visible. The presence of the species at one location can therefore be inferred from visual records derived from the panoramic views available from Google street view. We designed a standardized procedure allowing evaluating the presence of the PPM on a sampling grid covering the landscape under study. The outputs were compared to field data. We investigated two landscapes using grids of different extent and mesh size. Data derived from Google street view were highly similar to field data in the large-scale analysis based on a square grid with a mesh of 16 km (96% of matching records). Using a 2 km mesh size led to a strong divergence between field and Google-derived data (46% of matching records). We conclude that Google database might provide useful occurrence data for mapping the distribution of species which presence can be visually evaluated such as the PPM. However, the accuracy of the output strongly depends on the spatial scales considered and on the sampling grid used. Other factors such as the coverage of Google street view network with regards to sampling grid size and the spatial distribution of host trees with regards to road network may also be determinant. PMID:24130675
Large Scale Relationship between Aquatic Insect Traits and Climate.
Bhowmik, Avit Kumar; Schäfer, Ralf B
2015-01-01
Climate is the predominant environmental driver of freshwater assemblage pattern on large spatial scales, and traits of freshwater organisms have shown considerable potential to identify impacts of climate change. Although several studies suggest traits that may indicate vulnerability to climate change, the empirical relationship between freshwater assemblage trait composition and climate has been rarely examined on large scales. We compared the responses of the assumed climate-associated traits from six grouping features to 35 bioclimatic indices (~18 km resolution) for five insect orders (Diptera, Ephemeroptera, Odonata, Plecoptera and Trichoptera), evaluated their potential for changing distribution pattern under future climate change and identified the most influential bioclimatic indices. The data comprised 782 species and 395 genera sampled in 4,752 stream sites during 2006 and 2007 in Germany (~357,000 km² spatial extent). We quantified the variability and spatial autocorrelation in the traits and orders that are associated with the combined and individual bioclimatic indices. Traits of temperature preference grouping feature that are the products of several other underlying climate-associated traits, and the insect order Ephemeroptera exhibited the strongest response to the bioclimatic indices as well as the highest potential for changing distribution pattern. Regarding individual traits, insects in general and ephemeropterans preferring very cold temperature showed the highest response, and the insects preferring cold and trichopterans preferring moderate temperature showed the highest potential for changing distribution. We showed that the seasonal radiation and moisture are the most influential bioclimatic aspects, and thus changes in these aspects may affect the most responsive traits and orders and drive a change in their spatial distribution pattern. Our findings support the development of trait-based metrics to predict and detect climate-related changes of freshwater assemblages.
NASA Astrophysics Data System (ADS)
Brustolin, Marco C.; Thomas, Micheli C.; Mafra, Luiz L.; Lana, Paulo da Cunha
2014-08-01
Foraging macrofauna, such as the sand dollar Encope emarginata, can modify sediment properties and affect spatial distribution patterns of microphytobenthos and meiobenthos at different spatial scales. We adopted a spatial hierarchical approach composed of five spatial levels (km, 100 s m, 10 s m, 1 s m and cm) to describe variation patterns of microphytobenthos, meiobenthos and sediment variables in shallow subtidal regions in the subtropical Paranaguá Bay (Southern Brazil) with live E. emarginata (LE), dead E. emarginata (only skeletons - (DE), and no E. emarginata (WE). The overall structure of microphytobenthos and meiofauna was always less variable at WE and much of variation at the scale of 100 s m was related to variability within LE and DE, due to foraging activities or to the presence of shell hashes. Likewise, increased variability in chlorophyll-a and phaeopigment contents was observed among locations within LE, although textural parameters of sediment varied mainly at smaller scales. Variations within LE were related to changes on the amount and quality of food as a function of sediment heterogeneity induced by the foraging behavior of sand dollars. We provide strong evidence that top-down effects related to the occurrence of E. emarginata act in synergy with bottom-up structuring related to hydrodynamic processes in determining overall benthic spatial variability. Conversely, species richness is mainly influenced by environmental heterogeneity at small spatial scales (centimeters to meters), which creates a mosaic of microhabitats.
Need for multiscale planning for conservation of urban bats.
Gallo, Travis; Lehrer, Elizabeth W; Fidino, Mason; Kilgour, R Julia; Wolff, Patrick J; Magle, Seth B
2017-11-10
For over a century there have been continual efforts to incorporate nature into urban planning. These efforts (i.e., urban reconciliation) aim to manage and create habitats that support biodiversity within cities. Given that species select habitat at different spatial scales, understanding the scale at which urban species respond to their environment is critical to the success of urban reconciliation efforts. We assessed species-habitat relationships for common bat species at 50-m, 500-m, and 1 km spatial scales in the Chicago (U.S.A.) metropolitan area and predicted bat activity across the greater Chicago region. Habitat characteristics across all measured scales were important predictors of silver-haired bat (Lasionycteris noctivagans) and eastern red bat (Lasiurus borealis) activity, and big brown bat (Eptesicus fuscus) activity was significantly lower at urban sites relative to rural sites. Open vegetation had a negative effect on silver-haired bat activity at the 50-m scale but a positive effect at the 500-m scale, indicating potential shifts in the relative importance of some habitat characteristics at different scales. These results demonstrate that localized effects may be constrained by broader spatial patterns. Our findings highlight the importance of considering scale in urban reconciliation efforts and our landscape predictions provide information that can help prioritize urban conservation work. © 2017 Society for Conservation Biology.
Spatial Variability of Snowpack Properties On Small Slopes
NASA Astrophysics Data System (ADS)
Pielmeier, C.; Kronholm, K.; Schneebeli, M.; Schweizer, J.
The spatial variability of alpine snowpacks is created by a variety of parameters like deposition, wind erosion, sublimation, melting, temperature, radiation and metamor- phism of the snow. Spatial variability is thought to strongly control the avalanche initi- ation and failure propagation processes. Local snowpack measurements are currently the basis for avalanche warning services and there exist contradicting hypotheses about the spatial continuity of avalanche active snow layers and interfaces. Very little about the spatial variability of the snowpack is known so far, therefore we have devel- oped a systematic and objective method to measure the spatial variability of snowpack properties, layering and its relation to stability. For a complete coverage, the analysis of the spatial variability has to entail all scales from mm to km. In this study the small to medium scale spatial variability is investigated, i.e. the range from centimeters to tenths of meters. During the winter 2000/2001 we took systematic measurements in lines and grids on a flat snow test field with grid distances from 5 cm to 0.5 m. Fur- thermore, we measured systematic grids with grid distances between 0.5 m and 2 m in undisturbed flat fields and on small slopes above the tree line at the Choerbschhorn, in the region of Davos, Switzerland. On 13 days we measured the spatial pattern of the snowpack stratigraphy with more than 110 snow micro penetrometer measure- ments at slopes and flat fields. Within this measuring grid we placed 1 rutschblock and 12 stuffblock tests to measure the stability of the snowpack. With the large num- ber of measurements we are able to use geostatistical methods to analyse the spatial variability of the snowpack. Typical correlation lengths are calculated from semivari- ograms. Discerning the systematic trends from random spatial variability is analysed using statistical models. Scale dependencies are shown and recurring scaling patterns are outlined. The importance of the small and medium scale spatial variability for the larger (kilometer) scale spatial variability as well as for the avalanche formation are discussed. Finally, an outlook on spatial models for the snowpack variability is given.
NASA Astrophysics Data System (ADS)
Teige, V. E.; Weichsel, K.; Hooker, A.; Wooldridge, P. J.; Cohen, R. C.
2012-12-01
Efforts to curb greenhouse gas emissions, while global in their impacts, often focus on local and regional scales for execution and are dependent on the actions of communities and individuals. Evaluating the effectiveness of local policies requires observations with much higher spatial resolution than are currently available---kilometer scale. The Berkeley Atmospheric CO2 Observation Network (BEACON):, launched at the end of 2011, aims to provide measurements of urban-scale concentrations of CO2, temperature, pressure, relative humidity, O3, CO, and NO2 with sufficient spatial and temporal resolution to characterize the sources of CO2 within cities. Our initial deployment in Oakland, California uses ~40 sensor packages at a roughly 2 km spacing throughout the city. We will present an initial analysis of the vertical gradients and other spatial patterns observed to date.
A space-time multiscale modelling of Earth's gravity field variations
NASA Astrophysics Data System (ADS)
Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric
2017-04-01
The mass distribution within the Earth varies over a wide range of spatial and temporal scales, generating variations in the Earth's gravity field in space and time. These variations are monitored by satellites as the GRACE mission, with a 400 km spatial resolution and 10 days to 1 month temporal resolution. They are expressed in the form of gravity field models, often with a fixed spatial or temporal resolution. The analysis of these models allows us to study the mass transfers within the Earth system. Here, we have developed space-time multi-scale models of the gravity field, in order to optimize the estimation of gravity signals resulting from local processes at different spatial and temporal scales, and to adapt the time resolution of the model to its spatial resolution according to the satellites sampling. For that, we first build a 4D wavelet family combining spatial Poisson wavelets with temporal Haar wavelets. Then, we set-up a regularized inversion of inter-satellites gravity potential differences in a bayesian framework, to estimate the model parameters. To build the prior, we develop a spectral analysis, localized in time and space, of geophysical models of mass transport and associated gravity variations. Finally, we test our approach to the reconstruction of space-time variations of the gravity field due to hydrology. We first consider a global distribution of observations along the orbit, from a simplified synthetic hydrology signal comprising only annual variations at large spatial scales. Then, we consider a regional distribution of observations in Africa, and a larger number of spatial and temporal scales. We test the influence of an imperfect prior and discuss our results.
Spatial structures of stream and hillslope drainage networks following gully erosion after wildfire
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.
NASA Astrophysics Data System (ADS)
van der Velde, Y.; Rozemeijer, J. C.; de Rooij, G. H.; van Geer, F. C.; Torfs, P. J. J. F.; de Louw, P. G. B.
2011-03-01
Identifying effective measures to reduce nutrient loads of headwaters in lowland catchments requires a thorough understanding of flow routes of water and nutrients. In this paper we assess the value of nested-scale discharge and groundwater level measurements for the estimation of flow route volumes and for predictions of catchment discharge. In order to relate field-site measurements to the catchment-scale an upscaling approach is introduced that assumes that scale differences in flow route fluxes originate from differences in the relationship between groundwater storage and the spatial structure of the groundwater table. This relationship is characterized by the Groundwater Depth Distribution (GDD) curve that relates spatial variation in groundwater depths to the average groundwater depth. The GDD-curve was measured for a single field site (0.009 km2) and simple process descriptions were applied to relate groundwater levels to flow route discharges. This parsimonious model could accurately describe observed storage, tube drain discharge, overland flow and groundwater flow simultaneously with Nash-Sutcliff coefficients exceeding 0.8. A probabilistic Monte Carlo approach was applied to upscale field-site measurements to catchment scales by inferring scale-specific GDD-curves from the hydrographs of two nested catchments (0.4 and 6.5 km2). The estimated contribution of tube drain effluent (a dominant source for nitrates) decreased with increasing scale from 76-79% at the field-site to 34-61% and 25-50% for both catchment scales. These results were validated by demonstrating that a model conditioned on nested-scale measurements improves simulations of nitrate loads and predictions of extreme discharges during validation periods compared to a model that was conditioned on catchment discharge only.
Changes in streamflow contributions with increasing spatial scale in Thukela basin, South Africa
NASA Astrophysics Data System (ADS)
Mutema, Macdex; Chaplot, Vincent
2018-06-01
Sustainable management of river basins requires precise understanding of the origin and variability of water fluxes. Water samples were collected in Thukela Basin (30,000 km2), South Africa, over the 2012 rainy season, from fifteen 1 m2 runoff microplots (for OF), a 5-m deep piezometer (SW) and 20-m deep borehole (GW), in the basin headwater and nested catchment outlets (microcatchment, 0.23 km2; subcatchment, 1.20 km2; catchment, 9.75 km2; sub-basin, 253 km2). The water samples were analysed for Sodium (Na) and Silica (Si) concentrations using an inductively coupled-plasma emission spectrophotometry. End Member Mixing Analysis (EMMA), with Na and Si as tracers, was then used to quantify the water compartment contributions to river flow. The results showed a general decrease of unit-area runoff in downslope direction from 5.7 to 1.2 L m-2 day-1 at microplot and microcatchment level, respectively, to 1.4 L m-2 day-1 at the basin outlet. OF contributions averaged 61% at microcatchment, 79% at subcatchment, 40% at catchment, 78% at sub-basin and 67% at the basin outlet, which corresponded to 0.82, 0.26, 5 × 10-5, 2 × 10-3 and 9 × 10-5 L m-2 day-1, respectively. The respective SW contributions were 39% (0.38 L m-2 day-1), 18% (0.10 L m-2 day-1), 49% (5 × 10-5 L m-2 day-1), 15% (4 × 10-4 L m-2 day-1) and 33% (5 × 10-5 L m-2 day-1). GW contributions were much lower at all spatial scales, but showed a general increase with increasing contributing surface area from microcatchment to sub-basin outlet followed by a decrease to the basin outlet. The end-member contributions showed large spatial variations, hence longer-term research integrating more observation points is recommended to generate adequate data for development of prediction models for this important river basin. More research linking carbon, nutrient and pollutant fluxes to water dynamics is also recommended.
AmeriFlux US-PFa Park Falls/WLEF
DOE Office of Scientific and Technical Information (OSTI.GOV)
Desai, Ankur
This is the AmeriFlux version of the carbon flux data for the site US-PFa Park Falls/WLEF. Site Description - The flux footprint encompasses a highly heterogeneous landscape of upland forests and wetlands (forested and nonforested). The forests are mainly deciduous but also include substantial coniferous coverage. The upland/lowland variability occurs on spatial scales of a few hundred meters. This heterogeneous landscape is further complicated by a nonuniform, small scale mosaic of thinning and clearcutting of the forest. At larger scales (1 km or greater) the forest cover mosaic is quite homogeneous for many kilometers. The site was chosen not formore » study of a simple stand, but for upscaling experiments. The daytime fetch of flux measurements from the 396m level is on the order of 5-10 km, yielding a flux footprint roughly 100x the area of a typical stand-level flux tower. AC power (tower is a TV transmitter).« less
MOLECULAR GAS VELOCITY DISPERSIONS IN THE ANDROMEDA GALAXY
DOE Office of Scientific and Technical Information (OSTI.GOV)
Caldú-Primo, Anahi; Schruba, Andreas, E-mail: caldu@mpia.de, E-mail: schruba@mpe.mpg.de
In order to characterize the distribution of molecular gas in spiral galaxies, we study the line profiles of CO (1 – 0) emission in Andromeda, our nearest massive spiral galaxy. We compare observations performed with the IRAM 30 m single-dish telescope and with the CARMA interferometer at a common resolution of 23 arcsec ≈ 85 pc × 350 pc and 2.5 km s{sup −1}. When fitting a single Gaussian component to individual spectra, the line profile of the single dish data is a factor of 1.5 ± 0.4 larger than the interferometric data one. This ratio in line widths ismore » surprisingly similar to the ratios previously observed in two other nearby spirals, NGC 4736 and NGC 5055, but measured at ∼0.5–1 kpc spatial scale. In order to study the origin of the different line widths, we stack the individual spectra in five bins of increasing peak intensity and fit two Gaussian components to the stacked spectra. We find a unique narrow component of FWHM = 7.5 ± 0.4 km s{sup −1} visible in both the single dish and the interferometric data. In addition, a broad component with FWHM = 14.4 ± 1.5 km s{sup −1} is present in the single-dish data, but cannot be identified in the interferometric data. We interpret this additional broad line width component detected by the single dish as a low brightness molecular gas component that is extended on spatial scales >0.5 kpc, and thus filtered out by the interferometer. We search for evidence of line broadening by stellar feedback across a range of star formation rates but find no such evidence on ∼100 pc spatial scale when characterizing the line profile by a single Gaussian component.« less
Space and time scales of shoreline change at Cape Cod National Seashore, MA, USA
Allen, J.R.; LaBash, C.L.; List, J.H.; Kraus, Nicholas C.; McDougal, William G.
1999-01-01
Different processes cause patterns of shoreline change which are exhibited at different magnitudes and nested into different spatial and time scale hierarchies. The 77-km outer beach at Cape Cod National Seashore offers one of the few U.S. federally owned portions of beach to study shoreline change within the full range of sediment source and sink relationships, and barely affected by human intervention. 'Mean trends' of shoreline changes are best observed at long time scales but contain much spatial variation thus many sites are not equal in response. Long-term, earlier-noted trends are confirmed but the added quantification and resolution improves greatly the understanding of appropriate spatial and time scales of those processes driving bluff retreat and barrier island changes in both north and south depocenters. Shorter timescales allow for comparison of trends and uncertainty in shoreline change at local scales but are dependent upon some measure of storm intensity and seasonal frequency. Single-event shoreline survey results for one storm at daily intervals after the erosional phase suggest a recovery time for the system of six days, identifies three sites with abnormally large change, and that responses at these sites are spatially coherent for now unknown reasons. Areas near inlets are the most variable at all time scales. Hierarchies in both process and form are suggested.
Global-scale high-resolution ( 1 km) modelling of mean, maximum and minimum annual streamflow
NASA Astrophysics Data System (ADS)
Barbarossa, Valerio; Huijbregts, Mark; Hendriks, Jan; Beusen, Arthur; Clavreul, Julie; King, Henry; Schipper, Aafke
2017-04-01
Quantifying mean, maximum and minimum annual flow (AF) of rivers at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. AF metrics can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict AF metrics based on climate and catchment characteristics. Yet, so far, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. We developed global-scale regression models that quantify mean, maximum and minimum AF as function of catchment area and catchment-averaged slope, elevation, and mean, maximum and minimum annual precipitation and air temperature. We then used these models to obtain global 30 arc-seconds (˜ 1 km) maps of mean, maximum and minimum AF for each year from 1960 through 2015, based on a newly developed hydrologically conditioned digital elevation model. We calibrated our regression models based on observations of discharge and catchment characteristics from about 4,000 catchments worldwide, ranging from 100 to 106 km2 in size, and validated them against independent measurements as well as the output of a number of process-based global hydrological models (GHMs). The variance explained by our regression models ranged up to 90% and the performance of the models compared well with the performance of existing GHMs. Yet, our AF maps provide a level of spatial detail that cannot yet be achieved by current GHMs.
Cross-scale assessment of potential habitat shifts in a rapidly changing climate
Jarnevich, Catherine S.; Holcombe, Tracy R.; Bella, Elizabeth S.; Carlson, Matthew L.; Graziano, Gino; Lamb, Melinda; Seefeldt, Steven S.; Morisette, Jeffrey T.
2014-01-01
We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.
Anderson, Elizabeth P.; Pringle, Catherine M.; Freeman, Mary C.
2008-01-01
Costa Rica has recently experienced a rapid proliferation of dams for hydropower on rivers draining its northern Caribbean slope. In the Sarapiquí River Basin, eight hydropower plants were built between 1990 and 1999 and more projects are either under construction or proposed. The majority of these dams are small (<15 m tall) and operate as water diversion projects.While the potential environmental effects of individual projects are evaluated prior to dam construction, there is a need for consideration of the basin-scale ecological consequences of hydropower development. This study was a first attempt to quantify the extent of river fragmentation by dams in the Sarapiquí River Basin.Using simple spatial analyses, the length of river upstream from dams and the length of de-watered reaches downstream from dams was measured. Results indicated that there are currently 306.8 km of river (9.4% of the network) upstream from eight existing dams in the Sarapiquí River Basin and 30.6 km of rivers (0.9% of the network) with significantly reduced flow downstream from dams. Rivers upstream from dams primarily drain two life zones: Premontane Rain Forest (107.9 km) and Lower Montane Rain Forest (168.2 km).Simple spatial analyses can be used as a predictive or planning tool for considering the effects of future dams in a basin-scale context. In the Sarapiquí River Basin, we recommend that future dam projects be constructed on already dammed rivers to minimize additional river fragmentation and to protect remaining riverine connectivity.
Small-scale open ocean currents have large effects on wind wave heights
NASA Astrophysics Data System (ADS)
Ardhuin, Fabrice; Gille, Sarah T.; Menemenlis, Dimitris; Rocha, Cesar B.; Rascle, Nicolas; Chapron, Bertrand; Gula, Jonathan; Molemaker, Jeroen
2017-06-01
Tidal currents and large-scale oceanic currents are known to modify ocean wave properties, causing extreme sea states that are a hazard to navigation. Recent advances in the understanding and modeling capability of open ocean currents have revealed the ubiquitous presence of eddies, fronts, and filaments at scales 10-100 km. Based on realistic numerical models, we show that these structures can be the main source of variability in significant wave heights at scales less than 200 km, including important variations down to 10 km. Model results are consistent with wave height variations along satellite altimeter tracks, resolved at scales larger than 50 km. The spectrum of significant wave heights is found to be of the order of 70>
Mass balances of dissolved gases at river network scales across biomes.
NASA Astrophysics Data System (ADS)
Wollheim, W. M.; Stewart, R. J.; Sheehan, K.
2016-12-01
Estimating aquatic metabolism and gas fluxes at broad spatial scales is needed to evaluate the role of aquatic ecosystems in continental carbon cycles. We applied a river network model, FrAMES, to quantify the mass balances of dissolved oxygen at river network scales across five river networks in different biomes. The model accounts for hydrology; spatially varying re-aeration rates due to flow, slope, and water temperature; gas inputs via terrestrial runoff; variation in light due to canopy cover and water depth; benthic gross primary production; and benthic respiration. The model was parameterized using existing groundwater information and empirical relationships of GPP, R, and re-aeration, and was tested using dissolved oxygen patterns measured throughout river networks. We found that during summers, internal aquatic production dominates the river network mass balance of Kings Cr., Konza Prairie, KS (16.3 km2), whereas terrestrial inputs and aeration dominate the network mass balance at Coweeta Cr., Coweeta Forest, NC (15.7 km2). At network scales, both river networks are net heterotrophic, with Coweeta more so than Kings Cr. (P:R 0.6 vs. 0.7, respectively). The river network of Kings Creek showed higher network-scale GPP and R compared to Coweeta, despite having a lower drainage density because streams are on average wider so cumulative benthic surface areas are similar. Our findings suggest that the role of aquatic systems in watershed carbon balances will depend on interactions of drainage density, channel hydraulics, terrestrial vegetation, and biological activity.
Postaire, B; Gélin, P; Bruggemann, J H; Magalon, H
2017-04-01
Isolation by distance (IBD) is one of the main modes of differentiation in marine species, above all in species presenting low dispersal capacities. This study reports the genetic structuring in the tropical hydrozoan Lytocarpia brevirostris α (sensu Postaire et al, 2016b), a brooding species, from 13 populations in the Western Indian Ocean (WIO) and one from New Caledonia (Tropical Southwestern Pacific). At the local scale, populations rely on asexual propagation at short distance, which was not found at larger scales; identical genotypes were restricted to single populations. After the removal of repeated genotypes, all populations presented significant positive F IS values (between 0.094*** and 0.335***). Gene flow was extremely low at all spatial scales, between sites within islands (<10 km distance) and among islands (100 to>11 000 km distance), with significant pairwise F ST values (between 0.012*** and 0.560***). A general pattern of IBD was found at the Indo-Pacific scale, but also within sampled ecoregions of the WIO province. Clustering analyses identified each sampled island as an independent population, whereas analysis of molecular variance indicated that population genetic differentiation was significant at small (within island) and intermediate (among islands within province) spatial scales. The high population differentiation might reflect the life cycle of this brooding hydrozoan, possibly preventing regular dispersal at distances more than a few kilometres and probably leading to high cryptic diversity, each island housing an independent evolutionary lineage.
Global hydrodynamic modelling of flood inundation in continental rivers: How can we achieve it?
NASA Astrophysics Data System (ADS)
Yamazaki, D.
2016-12-01
Global-scale modelling of river hydrodynamics is essential for understanding global hydrological cycle, and is also required in interdisciplinary research fields . Global river models have been developed continuously for more than two decades, but modelling river flow at a global scale is still a challenging topic because surface water movement in continental rivers is a multi-spatial-scale phenomena. We have to consider the basin-wide water balance (>1000km scale), while hydrodynamics in river channels and floodplains is regulated by much smaller-scale topography (<100m scale). For example, heavy precipitation in upstream regions may later cause flooding in farthest downstream reaches. In order to realistically simulate the timing and amplitude of flood wave propagation for a long distance, consideration of detailed local topography is unavoidable. I have developed the global hydrodynamic model CaMa-Flood to overcome this scale-discrepancy of continental river flow. The CaMa-Flood divides river basins into multiple "unit-catchments", and assumes the water level is uniform within each unit-catchment. One unit-catchment is assigned to each grid-box defined at the typical spatial resolution of global climate models (10 100 km scale). Adopting a uniform water level in a >10km river segment seems to be a big assumption, but it is actually a good approximation for hydrodynamic modelling of continental rivers. The number of grid points required for global hydrodynamic simulations is largely reduced by this "unit-catchment assumption". Alternative to calculating 2-dimensional floodplain flows as in regional flood models, the CaMa-Flood treats floodplain inundation in a unit-catchment as a sub-grid physics. The water level and inundated area in each unit-catchment are diagnosed from water volume using topography parameters derived from high-resolution digital elevation models. Thus, the CaMa-Flood is at least 1000 times computationally more efficient compared to regional flood inundation models while the reality of simulated flood dynamics is kept. I will explain in detail how the CaMa-Flood model has been constructed from high-resolution topography datasets, and how the model can be used for various interdisciplinary applications.
Unleashing spatially distributed ecohydrology modeling using Big Data tools
NASA Astrophysics Data System (ADS)
Miles, B.; Idaszak, R.
2015-12-01
Physically based spatially distributed ecohydrology models are useful for answering science and management questions related to the hydrology and biogeochemistry of prairie, savanna, forested, as well as urbanized ecosystems. However, these models can produce hundreds of gigabytes of spatial output for a single model run over decadal time scales when run at regional spatial scales and moderate spatial resolutions (~100-km2+ at 30-m spatial resolution) or when run for small watersheds at high spatial resolutions (~1-km2 at 3-m spatial resolution). Numerical data formats such as HDF5 can store arbitrarily large datasets. However even in HPC environments, there are practical limits on the size of single files that can be stored and reliably backed up. Even when such large datasets can be stored, querying and analyzing these data can suffer from poor performance due to memory limitations and I/O bottlenecks, for example on single workstations where memory and bandwidth are limited, or in HPC environments where data are stored separately from computational nodes. The difficulty of storing and analyzing spatial data from ecohydrology models limits our ability to harness these powerful tools. Big Data tools such as distributed databases have the potential to surmount the data storage and analysis challenges inherent to large spatial datasets. Distributed databases solve these problems by storing data close to computational nodes while enabling horizontal scalability and fault tolerance. Here we present the architecture of and preliminary results from PatchDB, a distributed datastore for managing spatial output from the Regional Hydro-Ecological Simulation System (RHESSys). The initial version of PatchDB uses message queueing to asynchronously write RHESSys model output to an Apache Cassandra cluster. Once stored in the cluster, these data can be efficiently queried to quickly produce both spatial visualizations for a particular variable (e.g. maps and animations), as well as point time series of arbitrary variables at arbitrary points in space within a watershed or river basin. By treating ecohydrology modeling as a Big Data problem, we hope to provide a platform for answering transformative science and management questions related to water quantity and quality in a world of non-stationary climate.
NASA Astrophysics Data System (ADS)
Wang, J.; Su, Z.; Klein, P.; Thompson, A. F.; Menemenlis, D.; Fu, L. L.
2016-12-01
The major observational advance expected from the Surface Water and Ocean Topography (SWOT) altimeter, compared with existing altimeters, is that it will provide wide-swath (120 km) along-track data that permit the sampling of oceanic scales between 15 and 150km. The potential of this satellite mission is to understand the dynamical impact of these small scales on ocean dynamics. Such impact is known to affect the vertical velocity field (and therefore the vertical fluxes of ocean properties) and significantly affect both the inverse and direct kinetic energy cascades. The need to monitor these scales on a global scale is illustrated by the results of a realistic global ocean simulation. This model has 1/48-degree horizontal grid spacing, 90 vertical levels, and the inclusion of tidal forcing. This simulation reveals a strong seasonality of ocean dynamics at scales less than 100 km, not only in the previously documented regions, such as the Kuroshio extension, Gulf Stream, and subtropical gyres; but also in most other regions, such as most of the Southern Hemisphere and the North-East Atlantic. This strong seasonality, with a maximum amplitude consistently in winter, is associated with deep winter mixed-layer and energetic mesoscale eddies, pointing to mixed-layer instability as a major driver of the seasonality of dynamics at small scales. In addition to seasonal variations, strong intermittencies of ocean dynamics with a period of one to two weeks are also observed occasionally with the same amplitude as the seasonal variability. In this presentation, we discuss the consequences and the challenges posed by the strong spatial and temporal variability to SWOT data analysis.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Gang
Mid-latitude extreme weather events are responsible for a large part of climate-related damage. Yet large uncertainties remain in climate model projections of heat waves, droughts, and heavy rain/snow events on regional scales, limiting our ability to effectively use these projections for climate adaptation and mitigation. These uncertainties can be attributed to both the lack of spatial resolution in the models, and to the lack of a dynamical understanding of these extremes. The approach of this project is to relate the fine-scale features to the large scales in current climate simulations, seasonal re-forecasts, and climate change projections in a very widemore » range of models, including the atmospheric and coupled models of ECMWF over a range of horizontal resolutions (125 to 10 km), aqua-planet configuration of the Model for Prediction Across Scales and High Order Method Modeling Environments (resolutions ranging from 240 km – 7.5 km) with various physics suites, and selected CMIP5 model simulations. The large scale circulation will be quantified both on the basis of the well tested preferred circulation regime approach, and very recently developed measures, the finite amplitude Wave Activity (FAWA) and its spectrum. The fine scale structures related to extremes will be diagnosed following the latest approaches in the literature. The goal is to use the large scale measures as indicators of the probability of occurrence of the finer scale structures, and hence extreme events. These indicators will then be applied to the CMIP5 models and time-slice projections of a future climate.« less
Findings and Challenges in Fine-Resolution Large-Scale Hydrological Modeling
NASA Astrophysics Data System (ADS)
Her, Y. G.
2017-12-01
Fine-resolution large-scale (FL) modeling can provide the overall picture of the hydrological cycle and transport while taking into account unique local conditions in the simulation. It can also help develop water resources management plans consistent across spatial scales by describing the spatial consequences of decisions and hydrological events extensively. FL modeling is expected to be common in the near future as global-scale remotely sensed data are emerging, and computing resources have been advanced rapidly. There are several spatially distributed models available for hydrological analyses. Some of them rely on numerical methods such as finite difference/element methods (FDM/FEM), which require excessive computing resources (implicit scheme) to manipulate large matrices or small simulation time intervals (explicit scheme) to maintain the stability of the solution, to describe two-dimensional overland processes. Others make unrealistic assumptions such as constant overland flow velocity to reduce the computational loads of the simulation. Thus, simulation efficiency often comes at the expense of precision and reliability in FL modeling. Here, we introduce a new FL continuous hydrological model and its application to four watersheds in different landscapes and sizes from 3.5 km2 to 2,800 km2 at the spatial resolution of 30 m on an hourly basis. The model provided acceptable accuracy statistics in reproducing hydrological observations made in the watersheds. The modeling outputs including the maps of simulated travel time, runoff depth, soil water content, and groundwater recharge, were animated, visualizing the dynamics of hydrological processes occurring in the watersheds during and between storm events. Findings and challenges were discussed in the context of modeling efficiency, accuracy, and reproducibility, which we found can be improved by employing advanced computing techniques and hydrological understandings, by using remotely sensed hydrological observations such as soil moisture and radar rainfall depth and by sharing the model and its codes in public domain, respectively.
NASA Technical Reports Server (NTRS)
Davies, Roger
1994-01-01
The spatial autocorrelation functions of broad-band longwave and shortwave radiances measured by the Earth Radiation Budget Experiment (ERBE) are analyzed as a function of view angle in an investigation of the general effects of scene inhomogeneity on radiation. For nadir views, the correlation distance of the autocorrelation function is about 900 km for longwave radiance and about 500 km for shortwave radiance, consistent with higher degrees of freedom in shortwave reflection. Both functions rise monotonically with view angle, but there is a substantial difference in the relative angular dependence of the shortwave and longwave functions, especially for view angles less than 50 deg. In this range, the increase with angle of the longwave functions is found to depend only on the expansion of pixel area with angle, whereas the shortwave functions show an additional dependence on angle that is attributed to the occlusion of inhomogeneities by cloud height variations. Beyond a view angle of about 50 deg, both longwave and shortwave functions appear to be affected by cloud sides. The shortwave autocorrelation functions do not satisfy the principle of directional reciprocity, thereby proving that the average scene is horizontally inhomogeneous over the scale of an ERBE pixel (1500 sq km). Coarse stratification of the measurements by cloud amount, however, indicates that the average cloud-free scene does satisfy directional reciprocity on this scale.
NASA Astrophysics Data System (ADS)
Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard
2017-04-01
Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.
SSS variability inferred from recent SMOS reprocessing at CATDS
NASA Astrophysics Data System (ADS)
Boutin, Jacqueline; Vergely, Jean-Luc; Marchand, Stéphane; Tarot, Stéphane; Hasson, Audrey; Reverdin, Gilles
2017-04-01
The Soil Moisture and Ocean Salinity (SMOS) satellite mission has monitored sea surface salinity (SSS) over the global ocean for over 7 years. In this poster, we present results obtained at the LOCEAN/ACRI-st expertise center using recent CATDS (Centre Aval de Traitement des Données) SMOS RE05 reprocessing., We find that correction for systematic errors and removal of data contaminated by ice and radio frequency interferences in fresh regions (river mouths, high latitudes) has been improved with respect to SMOS CATDS RE04 reprocessing. We analyze SSS variability as observed by SMOS on a wide range of spatial and temporal scales using various statistical indicators such as mean, median, standard deviation, minimum, maximum values and spectral analysis. We compare them with ARGO interpolated fields (In Situ Analysis System fields) at global scale and with ship SSS transects from the GOSUD and ORE SSS data base. This allows us 1) to demonstrate and quantify the improvement of SMOS SSS fields with respect to earlier versions and 2) to study SSS variability, especially at spatial scales between 50km and 600km not well covered globally by in situ network. The complementarity of this information with respect to SMAP (Soil Moisture Active Passive) SSS fields will be discussed.
A new method for estimating carbon dioxide emissions from transportation at fine spatial scales
Shu, Yuqin; Reams, Margaret
2016-01-01
Detailed estimates of carbon dioxide (CO2) emissions at fine spatial scales are useful to both modelers and decision makers who are faced with the problem of global warming and climate change. Globally, transport related emissions of carbon dioxide are growing. This letter presents a new method based on the volume-preserving principle in the areal interpolation literature to disaggregate transportation-related CO2 emission estimates from the county-level scale to a 1 km2 grid scale. The proposed volume-preserving interpolation (VPI) method, together with the distance-decay principle, were used to derive emission weights for each grid based on its proximity to highways, roads, railroads, waterways, and airports. The total CO2 emission value summed from the grids within a county is made to be equal to the original county-level estimate, thus enforcing the volume-preserving property. The method was applied to downscale the transportation-related CO2 emission values by county (i.e. parish) for the state of Louisiana into 1 km2 grids. The results reveal a more realistic spatial pattern of CO2 emission from transportation, which can be used to identify the emission ‘hot spots’. Of the four highest transportation-related CO2 emission hotspots in Louisiana, high-emission grids literally covered the entire East Baton Rouge Parish and Orleans Parish, whereas CO2 emission in Jefferson Parish (New Orleans suburb) and Caddo Parish (city of Shreveport) were more unevenly distributed. We argue that the new method is sound in principle, flexible in practice, and the resultant estimates are more accurate than previous gridding approaches. PMID:26997973
NASA Astrophysics Data System (ADS)
Chen, X.; Song, X.; Shuai, P.; Hammond, G. E.; Ren, H.; Zachara, J. M.
2017-12-01
Hydrologic exchange flows (HEFs) in rivers play vital roles in watershed ecological and biogeochemical functions due to their strong capacity to attenuate contaminants and process significant quantities of carbon and nutrients. While most of existing HEF studies focus on headwater systems with the assumption of steady-state flow, there is lack of understanding of large-scale HEFs in high-order regulated rivers that experience high-frequency stage fluctuations. The large variability of HEFs is a result of interactions between spatial heterogeneity in hydrogeologic properties and temporal variation in river discharge induced by natural or anthropogenic perturbations. Our 9-year spatially distributed dataset (water elevation, specific conductance, and temperature) combined with mechanistic hydrobiogeochemical simulations have revealed complex spatial and temporal dynamics in km-scale HEFs and their significant impacts on contaminant plume mobility and hyporheic biogeochemical processes along the Hanford Reach. Extended multidirectional flow behaviors of unconfined, river corridor groundwater were observed hundreds of meters inland from the river shore resulting from discharge-dependent HEFs. An appropriately sized modeling domain to capture the impact of regional groundwater flow as well as knowledge of subsurface structures controlling intra-aquifer hydrologic connectivity were essential to realistically model transient storage in this large-scale river corridor. This work showed that both river water and mobile groundwater contaminants could serve as effective tracers of HEFs, thus providing valuable information for evaluating and validating the HEF models. Multimodal residence time distributions with long tails were resulted from the mixture of long and short exchange pathways, which consequently impact the carbon and nutrient cycling within the river corridor. Improved understanding of HEFs using integrated observational and modeling approaches sheds light on developing fundamental understanding of the influences of HEFs on water quality, nutrient dynamics, and ecosystem health in dynamic river corridor systems.
NASA Astrophysics Data System (ADS)
Schubert, J.; Sanders, B. F.; Andreadis, K.
2013-12-01
The Surface Water and Ocean Topography (SWOT) mission, currently under study by NASA (National Aeronautics and Space Administration) and CNES (Centre National d'Etudes Spatiales), is designed to provide global spatial measurements of surface water properties at resolutions better than 10 m and with centimetric accuracy. The data produced by SWOT will include irregularly spaced point clouds of the water surface height, with point spacings from roughly 2-50 m depending on a point's location within SWOT's swath. This could offer unprecedented insight into the spatial structure of rivers. Features that may be resolved include backwater profiles behind dams, drawdown profiles, uniform flow sections, critical flow sections, and even riffle-pool flow structures. In the event that SWOT scans a river during a major flood, it becomes possible to delineate the limits of the flood as well as the spatial structure of the water surface elevation, yielding insight into the dynamic interaction of channels and flood plains. The Platte River in Nebraska, USA, is a braided river with a width and slope of approximately 100 m and 100 cm/km, respectively. A 1 m resolution Digital Terrain Model (DTM) of the river basin, based on airborne lidar collected during low-flow conditions, was used to parameterize a two-dimensional, variable resolution, unstructured grid, hydrodynamic model that uses 3 m resolution triangles in low flow channels and 10 m resolution triangles in the floodplain. Use of a fine resolution mesh guarantees that local variability in topography is resolved, and after applying the hydrodynamic model, the effects of topographic variability are expressed as variability in the water surface height, depth-averaged velocity and flow depth. Flow is modeled over a reach length of 10 km for multi-day durations to capture both frequent (diurnal variations associated with regulated flow) and infrequent (extreme flooding) flow phenomena. Model outputs reveal a number of interesting features, including a high degree of variability in the water depth and velocity and lesser variability in the free-surface profile and river discharge. Hydraulic control sections are also revealed, and shown to depend on flow stage. Reach-averaging of model output is applied to study the macro-scale balance of forces in this system, and the scales at which such a force balance is appropriate. We find that the reach-average slope exhibits a declining reach-length dependence with increasing reach length, up to reach lengths of 1 km. Hence, 1 km appears to be the minimum appropriate length for reach-averaging, and at this scale, a diffusive-wave momentum balance is a reasonable approximation suitable for emerging models of discharge estimation that rely only on SWOT-observable river properties (width, height, slope, etc.).
NASA Astrophysics Data System (ADS)
Tormos, T.; Kosuth, P.; Souchon, Y.; Villeneuve, B.; Durrieu, S.; Chandesris, A.
2010-12-01
Preservation and restoration of river ecosystems require an improved understanding of the mechanisms through which they are influenced by landscape at multiple spatial scales and particularly at river corridor scale considering the role of riparian vegetation for regulating and protecting river ecological status and the relevance of this specific area for implementing efficient and realistic strategies. Assessing correctly this influence over large river networks involves accurate broad scale (i.e. at least regional) information on Land Cover within Riparian Areas (LCRA). As the structure of land cover along rivers is generally not accessible using moderate-scale satellite imagery, finer spatial resolution imagery and specific mapping techniques are needed. For this purpose we developed a generic multi-scale Object Based Image Analysis (OBIA) scheme able to produce LCRA maps in different geographic context by exploiting information available from very high spatial resolution imagery (satellite or airborne) and/or metric to decametric spatial thematic data on a given study zone thanks to fuzzy expert knowledge classification rules. A first experimentation was carried out on the Herault river watershed (southern of France), a 2650 square kilometers basin that presents a contrasted landscape (different ecoregions) and a total stream length of 1150 Km, using high and very high multispectral remotely-sensed images (10m Spot5 multispectral images and 0.5m aerial photography) and existing spatial thematic data. Application of the OBIA scheme produced a detailed (22 classes) LCRA map with an overall accuracy of 89% and a Kappa index of 83% according to a land cover pressures typology (six categories). A second experimentation (using the same data sources) was carried out on a larger test zone, a part of the Normandy river network (25 000 square kilometers basin; 6000 km long river network; 155 ecological stations). This second work aimed at elaborating a robust statistical eco-regional model to study links between land cover spatial indicators calculated at local and watershed scales, and river ecological status assessed with macroinvertebrate indicators. Application of the OBIA scheme produced a detailed (62 classes) LCRA map which allowed the model to highlight influence of specific land use patterns: (i) the significant beneficial effect of 20-m riparian tree vegetation strip near a station and 20-m riparian grassland strip along the upstream network of a station and (ii) the negative impact on river ecological status of urban areas and roads on the upstream flood plain of a station. Results of these two experimentations highlight that (i) the application of an OBIA scheme using multi-source spatial data provides an efficient approach for mapping and monitoring LCRA that can be implemented operationally at regional or national scale and (ii) and the interest of using LCRA-maps derived from very high spatial resolution imagery (satellite or airborne) and/or metric spatial thematic data to study landscape influence on river ecological status and support managers in the definition of optimized riparian preservation and restoration strategies.
A Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI)
NASA Astrophysics Data System (ADS)
Houborg, Rasmus; McCabe, Matthew F.; Gao, Feng
2016-05-01
Satellite remote sensing has been used successfully to map leaf area index (LAI) across landscapes, but advances are still needed to exploit multi-scale data streams for producing LAI at both high spatial and temporal resolution. A multi-scale Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI) has been developed to generate 4-day time-series of Landsat-scale LAI from existing medium resolution LAI products. STEM-LAI has been designed to meet the demands of applications requiring frequent and spatially explicit information, such as effectively resolving rapidly evolving vegetation dynamics at sub-field (30 m) scales. In this study, STEM-LAI is applied to Moderate Resolution Imaging Spectroradiometer (MODIS) based LAI data and utilizes a reference-based regression tree approach for producing MODIS-consistent, but Landsat-based, LAI. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is used to interpolate the downscaled LAI between Landsat acquisition dates, providing a high spatial and temporal resolution improvement over existing LAI products. STARFM predicts high resolution LAI by blending MODIS and Landsat based information from a common acquisition date, with MODIS data from a prediction date. To demonstrate its capacity to reproduce fine-scale spatial features observed in actual Landsat LAI, the STEM-LAI approach is tested over an agricultural region in Nebraska. The implementation of a 250 m resolution LAI product, derived from MODIS 1 km data and using a scale consistent approach based on the Normalized Difference Vegetation Index (NDVI), is found to significantly improve accuracies of spatial pattern prediction, with the coefficient of efficiency (E) ranging from 0.77-0.94 compared to 0.01-0.85 when using 1 km LAI inputs alone. Comparisons against an 11-year record of in-situ measured LAI over maize and soybean highlight the utility of STEM-LAI in reproducing observed LAI dynamics (both characterized by r2 = 0.86) over a range of plant development stages. Overall, STEM-LAI represents an effective downscaling and temporal enhancement mechanism that predicts in-situ measured LAI better than estimates derived through linear interpolation between Landsat acquisitions. This is particularly true when the in-situ measurement date is greater than 10 days from the nearest Landsat acquisition, with prediction errors reduced by up to 50%. With a streamlined and completely automated processing interface, STEM-LAI represents a flexible tool for LAI disaggregation in space and time that is adaptable to different land cover types, landscape heterogeneities, and cloud cover conditions.
Mapping regional soil water erosion risk in the Brittany-Loire basin for water management agency
NASA Astrophysics Data System (ADS)
Degan, Francesca; Cerdan, Olivier; Salvador-Blanes, Sébastien; Gautier, Jean-Noël
2014-05-01
Soil water erosion is one of the main degradation processes that affect soils through the removal of soil particles from the surface. The impacts for environment and agricultural areas are diverse, such as water pollution, crop yield depression, organic matter loss and reduction in water storage capacity. There is therefore a strong need to produce maps at the regional scale to help environmental policy makers and soil and water management bodies to mitigate the effect of water and soil pollution. Our approach aims to model and map soil erosion risk at regional scale (155 000 km²) and high spatial resolution (50 m) in the Brittany - Loire basin. The factors responsible for soil erosion are different according to the spatial and time scales considered. The regional scale entails challenges about homogeneous data sets availability, spatial resolution of results, various erosion processes and agricultural practices. We chose to improve the MESALES model (Le Bissonnais et al., 2002) to map soil erosion risk, because it was developed specifically for water erosion in agricultural fields in temperate areas. The MESALES model consists in a decision tree which gives for each combination of factors the corresponding class of soil erosion risk. Four factors that determine soil erosion risk are considered: soils, land cover, climate and topography. The first main improvement of the model consists in using newly available datasets that are more accurate than the initial ones. The datasets used cover all the study area homogeneously. Soil dataset has a 1/1 000 000 scale and attributes such as texture, soil type, rock fragment and parent material are used. The climate dataset has a spatial resolution of 8 km and a temporal resolution of mm/day for 12 years. Elevation dataset has a spatial resolution of 50 m. Three different land cover datasets are used where the finest spatial resolution is 50 m over three years. Using these datasets, four erosion factors are characterized and quantified: the soil factors (soil sealing, erodibility and runoff), the rate of land cover over three years for each season and for 77 land use classes, the topographic factor (slope and drainage area) and the climate hazard (seasonal amount and rainfall erosivity). These modifications of the original MESALES model allow to better represent erosion risk for arable and bare land. We validated model results by stakeholder consultations and meetings over all the study area. The model has finally been modified taking into account validation results. Results are provided with a spatial resolution of 1 km, and then integrated into 2121 catchments. An erosion risk map for each season and an annual erosion risk map are produced. These new maps allow to organize in hierarchy 2121 catchments into three erosion risk classes. In the annual erosion risk map, 347 catchments have the highest erosion risk, which corresponds to 16 % of total Brittany-Loire basin area. Water management agency now uses these maps to identify priority areas and to plan specific preservation practices.
Improving UK Chalk hydrometeorology across spatial scales using a small hydrometeorological network
NASA Astrophysics Data System (ADS)
Rosolem, Rafael; Iwema, Joost; Rahman, Mostaquimur; Desilets, Darin; Koltermann da Silva, Juliana
2016-04-01
Chalk in the UK acts as a primary aquifer providing up to 80% of the public water supply locally. Chalk outcrops are located over most of southern and eastern England. Despite its importance, the characterization of Chalk in hydrometeorological models is still very limited. There is a need for a comprehensive and coherent integration of observations and modeling efforts across spatial scales for better understanding Chalk hydrometeorology. Here we introduce the "A MUlti-scale Soil moisture-Evapotranspiration Dynamics" (AMUSED) project. AMUSED goal is to better identify the key dominant processes controlling changes in soil moisture and surface fluxes (e.g., evapotranspiration) across spatial scales by combining ground-based observations with hydrometeorological models and satellite remote sensing products. The AMUSED observational platform consists of three sites located in Upper Chalk region of the Lambourn Catchment located in southern England covering approximately 2 square-km characterized by distinct combinations of soil and vegetation types. The network includes standard meteorological measurements, an eddy covariance system for turbulent fluxes and cosmic-ray neutron sensors for integrated soil moisture estimates at intermediate scales. Here we present our initial results from our three sites.
Bridging the scales in a eulerian air quality model to assess megacity export of pollution
NASA Astrophysics Data System (ADS)
Siour, G.; Colette, A.; Menut, L.; Bessagnet, B.; Coll, I.; Meleux, F.
2013-08-01
In Chemistry Transport Models (CTMs), spatial scale interactions are often represented through off-line coupling between large and small scale models. However, those nested configurations cannot give account of the impact of the local scale on its surroundings. This issue can be critical in areas exposed to air mass recirculation (sea breeze cells) or around regions with sharp pollutant emission gradients (large cities). Such phenomena can still be captured by the mean of adaptive gridding, two-way nesting or using model nudging, but these approaches remain relatively costly. We present here the development and the results of a simple alternative multi-scale approach making use of a horizontal stretched grid, in the Eulerian CTM CHIMERE. This method, called "stretching" or "zooming", consists in the introduction of local zooms in a single chemistry-transport simulation. It allows bridging online the spatial scales from the city (∼1 km resolution) to the continental area (∼50 km resolution). The CHIMERE model was run over a continental European domain, zoomed over the BeNeLux (Belgium, Netherlands and Luxembourg) area. We demonstrate that, compared with one-way nesting, the zooming method allows the expression of a significant feedback of the refined domain towards the large scale: around the city cluster of BeNeLuX, NO2 and O3 scores are improved. NO2 variability around BeNeLux is also better accounted for, and the net primary pollutant flux transported back towards BeNeLux is reduced. Although the results could not be validated for ozone over BeNeLux, we show that the zooming approach provides a simple and immediate way to better represent scale interactions within a CTM, and constitutes a useful tool for apprehending the hot topic of megacities within their continental environment.
NASA Astrophysics Data System (ADS)
Orton, Glenn S.; Hansen, Candice; Caplinger, Michael; Ravine, Michael; Atreya, Sushil; Ingersoll, Andrew P.; Jensen, Elsa; Momary, Thomas; Lipkaman, Leslie; Krysak, Daniel; Zimdar, Robert; Bolton, Scott
2017-05-01
During Juno's first perijove encounter, the JunoCam instrument acquired the first images of Jupiter's polar regions at 50-70 km spatial scale at low emission angles. Poleward of 64-68° planetocentric latitude, where Jupiter's east-west banded structure breaks down, several types of discrete features appear on a darker background. Cyclonic oval features are clustered near both poles. Other oval-shaped features are also present, ranging in size from 2000 km down to JunoCam's resolution limits. The largest and brightest features often have chaotic shapes. Two narrow linear features in the north, associated with an overlying haze feature, traverse tens of degrees of longitude. JunoCam also detected an optically thin cloud or haze layer past the northern nightside terminator estimated to be 58 ± 21 km (approximately three scale heights) above the main cloud deck. JunoCam will acquire polar images on every perijove, allowing us to track the state and evolution of longer-lived features.
Global Autocorrelation Scales of the Partial Pressure of Oceanic CO2
NASA Technical Reports Server (NTRS)
Li, Zhen; Adamec, David; Takahashi, Taro; Sutherland, Stewart C.
2004-01-01
A global database of approximately 1.7 million observations of the partial pressure of carbon dioxide in surface ocean waters (pCO2) collected between 1970 and 2003 is used to estimate its spatial autocorrelation structure. The patterns of the lag distance where the autocorrelation exceeds 0.8 is similar to patterns in the spatial distribution of the first baroclinic Rossby radius of deformation indicating that ocean circulation processes play a significant role in determining the spatial variability of pCO2. For example, the global maximum of the distance at which autocorrelations exceed 0.8 averages about 140 km in the equatorial Pacific. Also, the lag distance at which the autocorrelation exceed 0.8 is greater in the vicinity of the Gulf Stream than it is near the Kuroshio, approximately 50 km near the Gulf Stream as opposed to 20 km near the Kuroshio. Separate calculations for times when the sun is north and south of the equator revealed no obvious seasonal dependence of the spatial autocorrelation scales. The pCO2 measurements at Ocean Weather Station (OWS) 'P', in the eastern subarctic Pacific (50 N, 145 W) is the only fixed location where an uninterrupted time series of sufficient length exists to calculate a meaningful temporal autocorrelation function for lags greater than a few days. The estimated temporal autocorrelation function at OWS 'P', is highly variable. A spectral analysis of the longest four pCO2 time series indicates a high level of variability occurring over periods from the atmospheric synoptic to the maximum length of the time series, in this case 42 days. It is likely that a relative peak in variability with a period of 3-6 days is related to atmospheric synoptic period variability and ocean mixing events due to wind stirring. However, the short length of available time series makes identifying temporal relationships between pCO2 and atmospheric or ocean processes problematic.
Sunarto, Sunarto; Kelly, Marcella J.; Parakkasi, Karmila; Klenzendorf, Sybille; Septayuda, Eka; Kurniawan, Harry
2012-01-01
The critically endangered Sumatran tiger (Panthera tigris sumatrae Pocock, 1929) is generally known as a forest-dependent animal. With large-scale conversion of forests into plantations, however, it is crucial for restoration efforts to understand to what extent tigers use modified habitats. We investigated tiger-habitat relationships at 2 spatial scales: occupancy across the landscape and habitat use within the home range. Across major landcover types in central Sumatra, we conducted systematic detection, non-detection sign surveys in 47, 17×17 km grid cells. Within each cell, we surveyed 40, 1-km transects and recorded tiger detections and habitat variables in 100 m segments totaling 1,857 km surveyed. We found that tigers strongly preferred forest and used plantations of acacia and oilpalm, far less than their availability. Tiger probability of occupancy covaried positively and strongly with altitude, positively with forest area, and negatively with distance-to-forest centroids. At the fine scale, probability of habitat use by tigers across landcover types covaried positively and strongly with understory cover and altitude, and negatively and strongly with human settlement. Within forest areas, tigers strongly preferred sites that are farther from water bodies, higher in altitude, farther from edge, and closer to centroid of large forest block; and strongly preferred sites with thicker understory cover, lower level of disturbance, higher altitude, and steeper slope. These results indicate that to thrive, tigers depend on the existence of large contiguous forest blocks, and that with adjustments in plantation management, tigers could use mosaics of plantations (as additional roaming zones), riparian forests (as corridors) and smaller forest patches (as stepping stones), potentially maintaining a metapopulation structure in fragmented landscapes. This study highlights the importance of a multi-spatial scale analysis and provides crucial information relevant to restoring tigers and other wildlife in forest and plantation landscapes through improvement in habitat extent, quality, and connectivity. PMID:22292063
Sunarto, Sunarto; Kelly, Marcella J; Parakkasi, Karmila; Klenzendorf, Sybille; Septayuda, Eka; Kurniawan, Harry
2012-01-01
The critically endangered Sumatran tiger (Panthera tigris sumatrae Pocock, 1929) is generally known as a forest-dependent animal. With large-scale conversion of forests into plantations, however, it is crucial for restoration efforts to understand to what extent tigers use modified habitats. We investigated tiger-habitat relationships at 2 spatial scales: occupancy across the landscape and habitat use within the home range. Across major landcover types in central Sumatra, we conducted systematic detection, non-detection sign surveys in 47, 17×17 km grid cells. Within each cell, we surveyed 40, 1-km transects and recorded tiger detections and habitat variables in 100 m segments totaling 1,857 km surveyed. We found that tigers strongly preferred forest and used plantations of acacia and oilpalm, far less than their availability. Tiger probability of occupancy covaried positively and strongly with altitude, positively with forest area, and negatively with distance-to-forest centroids. At the fine scale, probability of habitat use by tigers across landcover types covaried positively and strongly with understory cover and altitude, and negatively and strongly with human settlement. Within forest areas, tigers strongly preferred sites that are farther from water bodies, higher in altitude, farther from edge, and closer to centroid of large forest block; and strongly preferred sites with thicker understory cover, lower level of disturbance, higher altitude, and steeper slope. These results indicate that to thrive, tigers depend on the existence of large contiguous forest blocks, and that with adjustments in plantation management, tigers could use mosaics of plantations (as additional roaming zones), riparian forests (as corridors) and smaller forest patches (as stepping stones), potentially maintaining a metapopulation structure in fragmented landscapes. This study highlights the importance of a multi-spatial scale analysis and provides crucial information relevant to restoring tigers and other wildlife in forest and plantation landscapes through improvement in habitat extent, quality, and connectivity.
NASA Astrophysics Data System (ADS)
Rexer, Moritz; Hirt, Christian
2015-09-01
Classical degree variance models (such as Kaula's rule or the Tscherning-Rapp model) often rely on low-resolution gravity data and so are subject to extrapolation when used to describe the decay of the gravity field at short spatial scales. This paper presents a new degree variance model based on the recently published GGMplus near-global land areas 220 m resolution gravity maps (Geophys Res Lett 40(16):4279-4283, 2013). We investigate and use a 2D-DFT (discrete Fourier transform) approach to transform GGMplus gravity grids into degree variances. The method is described in detail and its approximation errors are studied using closed-loop experiments. Focus is placed on tiling, azimuth averaging, and windowing effects in the 2D-DFT method and on analytical fitting of degree variances. Approximation errors of the 2D-DFT procedure on the (spherical harmonic) degree variance are found to be at the 10-20 % level. The importance of the reference surface (sphere, ellipsoid or topography) of the gravity data for correct interpretation of degree variance spectra is highlighted. The effect of the underlying mass arrangement (spherical or ellipsoidal approximation) on the degree variances is found to be crucial at short spatial scales. A rule-of-thumb for transformation of spectra between spherical and ellipsoidal approximation is derived. Application of the 2D-DFT on GGMplus gravity maps yields a new degree variance model to degree 90,000. The model is supported by GRACE, GOCE, EGM2008 and forward-modelled gravity at 3 billion land points over all land areas within the SRTM data coverage and provides gravity signal variances at the surface of the topography. The model yields omission errors of 9 mGal for gravity (1.5 cm for geoid effects) at scales of 10 km, 4 mGal (1 mm) at 2-km scales, and 2 mGal (0.2 mm) at 1-km scales.
On the mesoscale monitoring capability of Argo floats in the Mediterranean Sea
NASA Astrophysics Data System (ADS)
Sánchez-Román, Antonio; Ruiz, Simón; Pascual, Ananda; Mourre, Baptiste; Guinehut, Stéphanie
2017-03-01
In this work a simplified observing system simulation experiment (OSSE) approach is used to investigate which Argo design sampling in the Mediterranean Sea would be necessary to properly capture the mesoscale dynamics in this basin. The monitoring of the mesoscale features is not an initial objective of the Argo network. However, it is an interesting question from the perspective of future network extensions in order to improve the ocean state estimates. The true field used to conduct the OSSEs is provided by a specific altimetry-gridded merged product for the Mediterranean Sea. Synthetic observations were obtained by sub-sampling this Nature Run
according to different configurations of the ARGO network. The observation errors required to perform the OSSEs were obtained through the comparison of sea level anomalies (SLAs) from altimetry and dynamic height anomalies (DHAs) computed from the real in situ Argo network. This analysis also contributes to validate satellite SLAs with an increased confidence. The simulation experiments show that a configuration similar to the current Argo array in the Mediterranean (with a spatial resolution of 2° × 2°) is only able to recover the large-scale signals of the basin. Increasing the spatial resolution to nearly 75 km × 75 km, allows the capture of most of the mesoscale signal in the basin and to retrieve the SLA field with a RMSE of 3 cm for spatial scales larger than 150 km, similar to those presently captured by the altimetry. This would represent a theoretical reduction of 40 % of the actual RMSE. Such a high-resolution Argo array composed of around 450 floats, cycling every 10 days, is expected to increase the actual network cost by approximately a factor of 6.
Research on relationships between dissolved nutrients and land use at the watershed scale is a high priority for protecting surface water quality. We measured dissolved nitrogen (DN) and ortho-phosphorus (P) along 130 km of the Calapooia River (Oregon, USA) and 44 of its sub-bas...
Multiple constraint analysis of regional land-surface carbon flux
D.P. Turner; M. Göckede; B.E. Law; W.D. Ritts; W.B. Cohen; Z. Yang; T. Hudiburg; R. Kennedy; M. Duane
2011-01-01
We applied and compared bottom-up (process model-based) and top-down (atmospheric inversion-based) scaling approaches to evaluate the spatial and temporal patterns of net ecosystem production (NEP) over a 2.5 Ã 105 km2 area (the state of Oregon) in the western United States. Both approaches indicated a carbon sink over this...
Sherley, Richard B; Botha, Philna; Underhill, Les G; Ryan, Peter G; van Zyl, Danie; Cockcroft, Andrew C; Crawford, Robert J M; Dyer, Bruce M; Cook, Timothée R
2017-12-01
Human activities are important drivers of marine ecosystem functioning. However, separating the synergistic effects of fishing and environmental variability on the prey base of nontarget predators is difficult, often because prey availability estimates on appropriate scales are lacking. Understanding how prey abundance at different spatial scales links to population change can help integrate the needs of nontarget predators into fisheries management by defining ecologically relevant areas for spatial protection. We investigated the local population response (number of breeders) of the Bank Cormorant (Phalacrocorax neglectus), a range-restricted endangered seabird, to the availability of its prey, the heavily fished west coast rock lobster (Jasus lalandii). Using Bayesian state-space modeled cormorant counts at 3 colonies, 22 years of fisheries-independent data on local lobster abundance, and generalized additive modeling, we determined the spatial scale pertinent to these relationships in areas with different lobster availability. Cormorant numbers responded positively to lobster availability in the regions with intermediate and high abundance but not where regime shifts and fishing pressure had depleted lobster stocks. The relationships were strongest when lobsters 20-30 km offshore of the colony were considered, a distance greater than the Bank Cormorant's foraging range when breeding, and may have been influenced by prey availability for nonbreeding birds, prey switching, or prey ecology. Our results highlight the importance of considering the scale of ecological relationships in marine spatial planning and suggest that designing spatial protection around focal species can benefit marine predators across their full life cycle. We propose the precautionary implementation of small-scale marine protected areas, followed by robust assessment and adaptive-management, to confirm population-level benefits for the cormorants, their prey, and the wider ecosystem, without negative impacts on local fisheries. © 2017 Society for Conservation Biology.
NASA Astrophysics Data System (ADS)
Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.
2017-12-01
Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.
Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi
2014-01-01
Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500–1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks. PMID:24824445
Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi
2014-01-01
Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500-1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks.
Estimating the volume and age of water stored in global lakes using a geo-statistical approach
Messager, Mathis Loïc; Lehner, Bernhard; Grill, Günther; Nedeva, Irena; Schmitt, Oliver
2016-01-01
Lakes are key components of biogeochemical and ecological processes, thus knowledge about their distribution, volume and residence time is crucial in understanding their properties and interactions within the Earth system. However, global information is scarce and inconsistent across spatial scales and regions. Here we develop a geo-statistical model to estimate the volume of global lakes with a surface area of at least 10 ha based on the surrounding terrain information. Our spatially resolved database shows 1.42 million individual polygons of natural lakes with a total surface area of 2.67 × 106 km2 (1.8% of global land area), a total shoreline length of 7.2 × 106 km (about four times longer than the world's ocean coastline) and a total volume of 181.9 × 103 km3 (0.8% of total global non-frozen terrestrial water stocks). We also compute mean and median hydraulic residence times for all lakes to be 1,834 days and 456 days, respectively. PMID:27976671
NASA Astrophysics Data System (ADS)
Skov, H.; Gunnlaugsson, T.; Budgell, W. P.; Horne, J.; Nøttestad, L.; Olsen, E.; Søiland, H.; Víkingsson, G.; Waring, G.
2008-01-01
The 2004 Mid-Atlantic Ridge (MAR)-ECO expedition on the R.V. G.O. Sars provided the first opportunity to correlate oceanic distributions of cetaceans with synoptic acoustic (ADCP to 700 m depth, multi-beam echosounders) measurements of high-resolution, three-dimensional (3D) potential habitat (spatial scale<100 km). The identified habitat features were tested with independent observations from the Icelandic combined cetacean and redfish cruises in 2001 and 2003 using data from a 3D ocean general circulation model of the MAR region (Regional Oceans Modelling System (ROMS) model 5 km resolution). The spatial autocorrelation of sampled encounter rates of sperm Physeter macrocephalus and sei whales Balaenoptera borealis indicated scale-dependent variability in the distribution of both species. Despite the large area surveyed, the observations of both species exhibited a strong small-scale structure (range parameter 20-50 km), indicating affinities to cross-seamount or cross-frontal structures. Potential cross-seamount and cross-frontal habitat structures were derived from the acoustic transect data by analysing fine-scale gradients in the 3D flow patterns and bathymetry, including interactions between frontal and topographic parameters. PLS regression was used to determine the potential habitat drivers of sperm and sei whales, both during the G.O. Sars cruise and during the Icelandic cruises in 2001 and 2003. The selected parameters, which reflected flow gradients interacting with the steep topography, were finally applied for modelling the habitat suitability of both target species along the northern MAR using Ecological Niche Factor Analysis. The results suggest aggregations of sperm and sei whales along the MAR are primarily associated with fine-scale frontal processes interacting with the topography in the upper 100 m of the water column just north of the Sub-Polar Front (SPF) and the Charlie-Gibbs Fracture Zone (CGFZ). As moderate and high habitat suitabilities were estimated only for areas downstream from the SPF, the findings suggest that the animals capitalise on secondary production maintained by enhanced primary production associated with the frontal processes in the upper part of the water column in the CGFZ and at the Faraday Seamounts. Further studies are encouraged to evaluate the importance of the bio-physical coupling, and the significance of small-scale frontal processes in the surface and subsurface waters north of the SPF for the transfer of energy to higher trophic levels in the North Atlantic.
NASA Astrophysics Data System (ADS)
Frolov, Vladimir
2015-06-01
In the review, the results of experimental studies of spatial structure of small-, middle-, and large scale plasma density perturbations induced in the ionosphere by its pumping by powerful HF O-mode (ordinary) radio waves, are analyzed. It is shown that the region with induced plasma density perturbations occupied all ionosphere body from its E-region up to the topside ionosphere in the height and it has the horizontal length of about of 300-500 km. Peculiarities of generation of artificial ionosphere irregularities of different scale-lengths in the magnetic zenith region are stated. Experimental results obtained under conditions of ionosphere periodical pumping when the generation of travel ionosphere disturbances is revealed are also discussed.
Spatial scaling of net primary productivity using subpixel landcover information
NASA Astrophysics Data System (ADS)
Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.
2008-10-01
Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.
Fullerton, A.H.; Torgersen, Christian E.; Lawer, J.J.; Steel, E. A.; Ebersole, J.L.; Lee, S.Y.
2018-01-01
Climate-change driven increases in water temperature pose challenges for aquatic organisms. Predictions of impacts typically do not account for fine-grained spatiotemporal thermal patterns in rivers. Patches of cooler water could serve as refuges for anadromous species like salmon that migrate during summer. We used high-resolution remotely sensed water temperature data to characterize summer thermal heterogeneity patterns for 11,308 km of second–seventh-order rivers throughout the Pacific Northwest and northern California (USA). We evaluated (1) water temperature patterns at different spatial resolutions, (2) the frequency, size, and spacing of cool thermal patches suitable for Pacific salmon (i.e., contiguous stretches ≥ 0.25 km, ≤ 15 °C and ≥ 2 °C, aooler than adjacent water), and (3) potential influences of climate change on availability of cool patches. Thermal heterogeneity was nonlinearly related to the spatial resolution of water temperature data, and heterogeneity at fine resolution (< 1 km) would have been difficult to quantify without spatially continuous data. Cool patches were generally > 2.7 and < 13.0 km long, and spacing among patches was generally > 5.7 and < 49.4 km. Thermal heterogeneity varied among rivers, some of which had long uninterrupted stretches of warm water ≥ 20 °C, and others had many smaller cool patches. Our models predicted little change in future thermal heterogeneity among rivers, but within-river patterns sometimes changed markedly compared to contemporary patterns. These results can inform long-term monitoring programs as well as near-term climate-adaptation strategies.
Miller, Jennifer R B; Jhala, Yadvendradev V; Jena, Jyotirmay; Schmitz, Oswald J
2015-03-01
Innovative conservation tools are greatly needed to reduce livelihood losses and wildlife declines resulting from human-carnivore conflict. Spatial risk modeling is an emerging method for assessing the spatial patterns of predator-prey interactions, with applications for mitigating carnivore attacks on livestock. Large carnivores that ambush prey attack and kill over small areas, requiring models at fine spatial grains to predict livestock depredation hot spots. To detect the best resolution for predicting where carnivores access livestock, we examined the spatial attributes associated with livestock killed by tigers in Kanha Tiger Reserve, India, using risk models generated at 20, 100, and 200-m spatial grains. We analyzed land-use, human presence, and vegetation structure variables at 138 kill sites and 439 random sites to identify key landscape attributes where livestock were vulnerable to tigers. Land-use and human presence variables contributed strongly to predation risk models, with most variables showing high relative importance (≥0.85) at all spatial grains. The risk of a tiger killing livestock increased near dense forests and near the boundary of the park core zone where human presence is restricted. Risk was nonlinearly related to human infrastructure and open vegetation, with the greatest risk occurring 1.2 km from roads, 1.1 km from villages, and 8.0 km from scrubland. Kill sites were characterized by denser, patchier, and more complex vegetation with lower visibility than random sites. Risk maps revealed high-risk hot spots inside of the core zone boundary and in several patches in the human-dominated buffer zone. Validation against known kills revealed predictive accuracy for only the 20 m model, the resolution best representing the kill stage of hunting for large carnivores that ambush prey, like the tiger. Results demonstrate that risk models developed at fine spatial grains can offer accurate guidance on landscape attributes livestock should avoid to minimize human-carnivore conflict.
Latitude delineates patterns of biogeography in terrestrial Streptomyces.
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.
Predicting minimum habitat characteristics for the Indiana bat in the Champlain Valley
Watrous, K.S.; Donovan, T.M.; Mickey, R.M.; Darling, S.R.; Hicks, A.C.; Von Oettingen, S. L.
2006-01-01
Predicting potential habitat across a landscape for rare species is extremely challenging. However, partitioned Mahalanobis D2 methods avoid pitfalls commonly encountered when surveying rare species by using data collected only at known species locations. Minimum habitat requirements are then determined by examining a principal components analysis to find consistent habitat characteristics across known locations. We used partitioned D 2 methods to examine minimum habitat requirements of Indiana bats (Myotis sodalis) in the Champlain Valley of Vermont and New York, USA, across 7 spatial scales and map potential habitat for the species throughout the same area. We radiotracked 24 female Indiana bats to their roost trees and across their nighttime foraging areas to collect habitat characteristics at 7 spatial scales: 1) roost trees, 2) 0.1-ha circular plots surrounding the roost trees, 3) home ranges, and 4-7) 0.5-km, 1-km, 2-km, and 3-km buffers surrounding the roost tree. Roost trees (n = 50) typically were tall, dead, large-diameter trees with exfoliating bark, located at low elevations and close to water. Trees surrounding roosts typically were smaller in diameter and shorter in height, but they had greater soundness than the roost trees. We documented 14 home ranges in areas of diverse, patchy land cover types that were close to water with east-facing aspects. Across all landscape extents, area of forest within roost-tree buffers and the aspect across those buffers were the most consistent features. Predictive maps indicated that suitable habitat ranged from 4.7-8.1% of the area examined within the Champlain Valley. These habitat models further understanding of Indiana bat summer habitat by indicating minimum habitat characteristics at multiple scales and can be used to aid management decisions by highlighting potential habitat. Nonetheless, information on juvenile production and recruitment is lacking; therefore, assessments of Indiana bat habitat quality in the region are still incomplete.
NASA Technical Reports Server (NTRS)
Ott, L.; Putman, B.; Collatz, J.; Gregg, W.
2012-01-01
Column CO2 observations from current and future remote sensing missions represent a major advancement in our understanding of the carbon cycle and are expected to help constrain source and sink distributions. However, data assimilation and inversion methods are challenged by the difference in scale of models and observations. OCO-2 footprints represent an area of several square kilometers while NASA s future ASCENDS lidar mission is likely to have an even smaller footprint. In contrast, the resolution of models used in global inversions are typically hundreds of kilometers wide and often cover areas that include combinations of land, ocean and coastal areas and areas of significant topographic, land cover, and population density variations. To improve understanding of scales of atmospheric CO2 variability and representativeness of satellite observations, we will present results from a global, 10-km simulation of meteorology and atmospheric CO2 distributions performed using NASA s GEOS-5 general circulation model. This resolution, typical of mesoscale atmospheric models, represents an order of magnitude increase in resolution over typical global simulations of atmospheric composition allowing new insight into small scale CO2 variations across a wide range of surface flux and meteorological conditions. The simulation includes high resolution flux datasets provided by NASA s Carbon Monitoring System Flux Pilot Project at half degree resolution that have been down-scaled to 10-km using remote sensing datasets. Probability distribution functions are calculated over larger areas more typical of global models (100-400 km) to characterize subgrid-scale variability in these models. Particular emphasis is placed on coastal regions and regions containing megacities and fires to evaluate the ability of coarse resolution models to represent these small scale features. Additionally, model output are sampled using averaging kernels characteristic of OCO-2 and ASCENDS measurement concepts to create realistic pseudo-datasets. Pseudo-data are averaged over coarse model grid cell areas to better understand the ability of measurements to characterize CO2 distributions and spatial gradients on both short (daily to weekly) and long (monthly to seasonal) time scales
Waves in the Mesosphere of Venus as seen by the Venus Express Radio Science Experiment VeRa
NASA Astrophysics Data System (ADS)
Tellmann, Silvia; Häusler, B.; Hinson, D. P.; Tyler, G.; Andert, T. P.; Bird, M. K.; Imamura, T.; Pätzold, M.; Remus, S.
2013-10-01
The Venus Express Radio Science Experiment (VeRa) has retrieved more than 700 profiles of the mesosphere and troposphere of Venus. These profiles cover a wide range of latitudes and local times, enabling study of atmospheric wave phenomena over a range spatial scales at altitudes of 40-90 km. In addition to quasi-horizontal waves and eddies on near planetary scales, diurnally forced eddies and thermal tides, small-scale gravity waves, and turbulence play a significant role in the development and maintenance of atmospheric super-rotation. Small-scale temperature variations with vertical wavelengths of 4 km or less have wave amplitudes reaching TBD km in the stable atmosphere above the tropopause, in contrast with much weaker temperature perturbations observed in the middle cloud layer below. The strength of gravity waves increases with latitude in both hemispheres. The results suggest that convection at low latitudes and topographical forcing at high northern latitudes—possibly in combination with convection and/or Kelvin-Helmholtz instabilities—play key roles in the genesis of gravity waves. Further, thermal tides also play an important role in the mesosphere. Diurnal and semi-diurnal wave modes are observed at different latitudes and altitudes. The latitudinal and height dependence of the thermal tide modes will be investigated.
Estimates of reservoir methane emissions based on a spatially ...
Global estimates of methane (CH4) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra-reservoir spatial variability. Reservoir-scale emission rates are often estimated by extrapolating from measurement made at a few locations; however, error and bias associated with this approach can be large and difficult to quantify. Here we use a generalized random tessellation survey (GRTS) design to generate estimates of central tendency and variance at multiple spatial scales in a reservoir. GRTS survey designs are probabilistic and spatially balanced which eliminates bias associated with expert judgment in site selection. GRTS surveys also allow for variance estimates that account for spatial pattern in emission rates. Total CH4 emission rates (i.e. sum of ebullition and diffusive emissions) were 4.8 (±2.1), 33.0 (±10.7), and 8.3 (±2.2) mg CH4 m-2 h-1 in open-waters, tributary associated areas, and the entire reservoir for the period in August 2014 during which 115 sites were sampled across an 7.98 km2 reservoir in Southwestern, Ohio, USA. Tributary areas occupy 12% of the reservoir surface, but were the source of 41% of total CH4 emissions, highlighting the importance of riverine-lacustrine transition zones. Ebullition accounted for >90% of CH4 emission at all spatial scales. Confidence interval estimates that incorporated spatial pattern in CH4 emissions were up to 29% narrower than when spatial independence
Hernández-Ceballos, M A; Skjøth, C A; García-Mozo, H; Bolívar, J P; Galán, C
2014-12-01
Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.
Singh, Minerva; Friess, Daniel A.; Vilela, Bruno; Alban, Jose Don T. De; Monzon, Angelica Kristina V.; Veridiano, Rizza Karen A.; Tumaneng, Roven D.
2017-01-01
This study maps distribution and spatial congruence between Above-Ground Biomass (AGB) and species richness of IUCN listed conservation-dependent and endemic avian fauna in Palawan, Philippines. Grey Level Co-Occurrence Texture Matrices (GLCMs) extracted from Landsat and ALOS-PALSAR were used in conjunction with local field data to model and map local-scale field AGB using the Random Forest algorithm (r = 0.92 and RMSE = 31.33 Mg·ha-1). A support vector regression (SVR) model was used to identify the factors influencing variation in avian species richness at a 1km scale. AGB is one of the most important determinants of avian species richness for the study area. Topographic factors and anthropogenic factors such as distance from the roads were also found to strongly influence avian species richness. Hotspots of high AGB and high species richness concentration were mapped using hotspot analysis and the overlaps between areas of high AGB and avian species richness was calculated. Results show that the overlaps between areas of high AGB with high IUCN red listed avian species richness and endemic avian species richness were fairly limited at 13% and 8% at the 1-km scale. The overlap between 1) low AGB and low IUCN richness, and 2) low AGB and low endemic avian species richness was higher at 36% and 12% respectively. The enhanced capacity to spatially map the correlation between AGB and avian species richness distribution will further assist the conservation and protection of forest areas and threatened avian species. PMID:29206228
NASA Astrophysics Data System (ADS)
Hernández-Ceballos, M. A.; Skjøth, C. A.; García-Mozo, H.; Bolívar, J. P.; Galán, C.
2014-12-01
Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.
Gustafson, E.J.; Knutson, M.G.; Niemi, G.J.; Friberg, M.
2002-01-01
We constructed alternative spatial models at two scales to predict Brown-headed Cowbird (Molothrus ater) parasitism rates from land cover maps. The local-scale models tested competing hypotheses about the relationship between cowbird parasitism and distance of host nests from a forest edge (forest-nonforest boundary). The landscape models tested competing hypotheses about how landscape features (e.g., forests, agricultural fields) interact to determine rates of cowbird parasitism. The models incorporate spatial neighborhoods with a radius of 2.5 km in their formulation, reflecting the scale of the majority of cowbird commuting activity. Field data on parasitism by cowbirds (parasitism rate and number of cowbird eggs per nest) were collected at 28 sites in the Driftless Area Ecoregion of Wisconsin, Minnesota, and Iowa and were compared to the predictions of the alternative models. At the local scale, there was a significant positive relationship between cowbird parasitism and mean distance of nest sites from the forest edge. At the landscape scale, the best fitting models were the forest-dependent and forest-fragmentation-dependent models, in which more heavily forested and less fragmented landscapes had higher parasitism rates. However, much of the explanatory power of these models results from the inclusion of the local-scale relationship in these models. We found lower rates of cowbird parasitism than did most Midwestern studies, and we identified landscape patterns of cowbird parasitism that are opposite to those reported in several other studies of Midwestern songbirds. We caution that cowbird parasitism patterns can be unpredictable, depending upon ecoregional location and the spatial extent, and that our models should be tested in other ecoregions before they are applied there. Our study confirms that cowbird biology has a strong spatial component, and that improved spatial models applied at multiple spatial scales will be required to predict the effects of landscape and forest management on cowbird parasitism of forest birds.
Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)
NASA Technical Reports Server (NTRS)
Cahalan, R. F.; Morcrette, J. J.
1999-01-01
Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better understanding of the upscale cascade and suggesting new cloud-radiation parameterizations for climate models.
Polansky, Leo; Kilian, Werner; Wittemyer, George
2015-01-01
Spatial memory facilitates resource acquisition where resources are patchy, but how it influences movement behaviour of wide-ranging species remains to be resolved. We examined African elephant spatial memory reflected in movement decisions regarding access to perennial waterholes. State–space models of movement data revealed a rapid, highly directional movement behaviour almost exclusively associated with visiting perennial water. Behavioural change point (BCP) analyses demonstrated that these goal-oriented movements were initiated on average 4.59 km, and up to 49.97 km, from the visited waterhole, with the closest waterhole accessed 90% of the time. Distances of decision points increased when switching to different waterholes, during the dry season, or for female groups relative to males, while selection of the closest waterhole decreased when switching. Overall, our analyses indicated detailed spatial knowledge over large scales, enabling elephants to minimize travel distance through highly directional movement when accessing water. We discuss the likely cognitive and socioecological mechanisms driving these spatially precise movements that are most consistent with our findings. By applying modern analytic techniques to high-resolution movement data, this study illustrates emerging approaches for studying how cognition structures animal movement behaviour in different ecological and social contexts. PMID:25808888
Spatial relationships between alcohol-related road crashes and retail alcohol availability.
Morrison, Christopher; Ponicki, William R; Gruenewald, Paul J; Wiebe, Douglas J; Smith, Karen
2016-05-01
This study examines spatial relationships between alcohol outlet density and the incidence of alcohol-related crashes. The few prior studies conducted in this area used relatively large spatial units; here we use highly resolved units from Melbourne, Australia (Statistical Area level 1 [SA1] units: mean land area=0.5 km(2); SD=2.2 km(2)), in order to assess different micro-scale spatial relationships for on- and off-premise outlets. Bayesian conditional autoregressive Poisson models were used to assess cross-sectional relationships of three-year counts of alcohol-related crashes (2010-2012) attended by Ambulance Victoria paramedics to densities of bars, restaurants, and off-premise outlets controlling for other land use, demographic and roadway characteristics. Alcohol-related crashes were not related to bar density within local SA1 units, but were positively related to bar density in adjacent SA1 units. Alcohol-related crashes were negatively related to off-premise outlet density in local SA1 units. Examined in one metropolitan area using small spatial units, bar density is related to greater crash risk in surrounding areas. Observed negative relationships for off-premise outlets may be because the origins and destinations of alcohol-affected journeys are in distal locations relative to outlets. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Forecasting climate change impacts on plant populations over large spatial extents
Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; ...
2016-10-24
Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less
Forecasting climate change impacts on plant populations over large spatial extents
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.
Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less
Forecasting climate change impacts on plant populations over large spatial extents
Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; Homer, Collin G.; Kleinhesselink, Andrew R.; Adler, Peter B.
2016-01-01
Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.
Spatial scaling of bacterial community diversity at shallow hydrothermal vents: a global comparison
NASA Astrophysics Data System (ADS)
Pop Ristova, P.; Hassenrueck, C.; Molari, M.; Fink, A.; Bühring, S. I.
2016-02-01
Marine shallow hydrothermal vents are extreme environments, often characterized by discharge of fluids with e.g. high temperatures, low pH, and laden with elements toxic to higher organisms. They occur at continental margins around the world's oceans, but represent fragmented, isolated habitats of locally small areal coverage. Microorganisms contribute the main biomass at shallow hydrothermal vent ecosystems and build the basis of the food chain by autotrophic fixation of carbon both via chemosynthesis and photosynthesis, occurring simultaneously. Despite their importance and unique capacity to adapt to these extreme environments, little is known about the spatial scales on which the alpha- and beta-diversity of microbial communities vary at shallow vents, and how the geochemical habitat heterogeneity influences shallow vent biodiversity. Here for the first time we investigated the spatial scaling of microbial biodiversity patterns and their interconnectivity at geochemically diverse shallow vents on a global scale. This study presents data on the comparison of bacterial community structures on large (> 1000 km) and small (0.1 - 100 m) spatial scales as derived from ARISA and Illumina sequencing. Despite the fragmented global distribution of shallow hydrothermal vents, similarity of vent bacterial communities decreased with geographic distance, confirming the ubiquity of distance-decay relationship. Moreover, at all investigated vents, pH was the main factor locally structuring these communities, while temperature influenced both the alpha- and beta-diversity.
NASA Astrophysics Data System (ADS)
Singh, G.; Das, N. N.; Panda, R. K.; Mohanty, B.; Entekhabi, D.; Bhattacharya, B. K.
2016-12-01
Soil moisture status at high resolution (1-10 km) is vital for hydrological, agricultural and hydro-metrological applications. The NASA Soil Moisture Active Passive (SMAP) mission had potential to provide reliable soil moisture estimate at finer spatial resolutions (3 km and 9 km) at the global extent, but suffered a malfunction of its radar, consequently making the SMAP mission observations only from radiometer that are of coarse spatial resolution. At present, the availability of high-resolution soil moisture product is limited, especially in developing countries like India, which greatly depends on agriculture for sustaining a huge population. Therefore, an attempt has been made in the reported study to combine the C-band synthetic aperture radar (SAR) data from Radar Imaging Satellite (RISAT) of the Indian Space Research Organization (ISRO) with the SMAP mission L-band radiometer data to obtain high-resolution (1 km and 3 km) soil moisture estimates. In this study, a downscaling approach (Active-Passive Algorithm) implemented for the SMAP mission was used to disaggregate the SMAP radiometer brightness temperature (Tb) using the fine resolution SAR backscatter (σ0) from RISAT. The downscaled high-resolution Tb was then subjected to tau-omega model in conjunction with high-resolution ancillary data to retrieve soil moisture at 1 and 3 km scale. The retrieved high-resolution soil moisture estimates were then validated with ground based soil moisture measurement under different hydro-climatic regions of India. Initial results show tremendous potential and reasonable accuracy for the retrieved soil moisture at 1 km and 3 km. It is expected that ISRO will implement this approach to produce high-resolution soil moisture estimates for the Indian subcontinent.
NASA Astrophysics Data System (ADS)
Priebe, Elizabeth H.; Neville, C. J.; Rudolph, D. L.
2018-03-01
The spatial coverage of hydraulic conductivity ( K) values for large-scale groundwater investigations is often poor because of the high costs associated with hydraulic testing and the large areas under investigation. Domestic water wells are ubiquitous and their well logs represent an untapped resource of information that includes mandatory specific-capacity tests, from which K can be estimated. These specific-capacity tests are routinely conducted at such low pumping rates that well losses are normally insignificant. In this study, a simple and practical approach to augmenting high-quality K values with reconnaissance-level K values from water-well specific-capacity tests is assessed. The integration of lesser quality K values from specific-capacity tests with a high-quality K data set is assessed through comparisons at two different scales: study-area-wide (a 600-km2 area in Ontario, Canada) and in a single geological formation within a portion of the broader study area (200 km2). Results of the comparisons demonstrate that reconnaissance-level K estimates from specific-capacity tests approximate the ranges and distributions of the high-quality K values. Sufficient detail about the physical basis and assumptions that are invoked in the development of the approach are presented here so that it can be applied with confidence by practitioners seeking to enhance their spatial coverage of K values with specific-capacity tests.
The assessment of spatial distribution of soil salinity risk using neural network.
Akramkhanov, Akmal; Vlek, Paul L G
2012-04-01
Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.
An index of floodplain surface complexity
Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.
2016-01-01
Floodplain surface topography is an important component of floodplain ecosystems. It is the primary physical template upon which ecosystem processes are acted out, and complexity in this template can contribute to the high biodiversity and productivity of floodplain ecosystems. There has been a limited appreciation of floodplain surface complexity because of the traditional focus on temporal variability in floodplains as well as limitations to quantifying spatial complexity. An index of floodplain surface complexity (FSC) is developed in this paper and applied to eight floodplains from different geographic settings. The index is based on two key indicators of complexity, variability in surface geometry (VSG) and the spatial organisation of surface conditions (SPO), and was determined at three sampling scales. FSC, VSG, and SPO varied between the eight floodplains and these differences depended upon sampling scale. Relationships between these measures of spatial complexity and seven geomorphological and hydrological drivers were investigated. There was a significant decline in all complexity measures with increasing floodplain width, which was explained by either a power, logarithmic, or exponential function. There was an initial rapid decline in surface complexity as floodplain width increased from 1.5 to 5 km, followed by little change in floodplains wider than 10 km. VSG also increased significantly with increasing sediment yield. No significant relationships were determined between any of the four hydrological variables and floodplain surface complexity.
A multiscale analysis of coral reef topographic complexity using lidar-derived bathymetry
Zawada, D.G.; Brock, J.C.
2009-01-01
Coral reefs represent one of the most irregular substrates in the marine environment. This roughness or topographic complexity is an important structural characteristic of reef habitats that affects a number of ecological and environmental attributes, including species diversity and water circulation. Little is known about the range of topographic complexity exhibited within a reef or between different reef systems. The objective of this study was to quantify topographic complexity for a 5-km x 5-km reefscape along the northern Florida Keys reef tract, over spatial scales ranging from meters to hundreds of meters. The underlying dataset was a 1-m spatial resolution, digital elevation model constructed from lidar measurements. Topographic complexity was quantified using a fractal algorithm, which provided a multi-scale characterization of reef roughness. The computed fractal dimensions (D) are a measure of substrate irregularity and are bounded between values of 2 and 3. Spatial patterns in D were positively correlated with known reef zonation in the area. Landward regions of the study site contain relatively smooth (D ??? 2.35) flat-topped patch reefs, which give way to rougher (D ??? 2.5), deep, knoll-shaped patch reefs. The seaward boundary contains a mixture of substrate features, including discontinuous shelf-edge reefs, and exhibits a corresponding range of roughness values (2.28 ??? D ??? 2.61). ?? 2009 Coastal Education and Research Foundation.
Tan, Xiangping; Xie, Baoni; Wang, Junxing; He, Wenxiang; Wang, Xudong; Wei, Gehong
2014-01-01
Here the spatial distribution of soil enzymatic properties in agricultural land was evaluated on a county-wide (567 km(2)) scale in Changwu, Shaanxi Province, China. The spatial variations in activities of five hydrolytic enzymes were examined using geostatistical methods. The relationships between soil enzyme activities and other soil properties were evaluated using both an integrated total enzyme activity index (TEI) and the geometric mean of enzyme activities (GME). At the county scale, soil invertase, phosphatase, and catalase activities were moderately spatially correlated, whereas urease and dehydrogenase activities were weakly spatially correlated. Correlation analysis showed that both TEI and GME were better correlated with selected soil physicochemical properties than single enzyme activities. Multivariate regression analysis showed that soil OM content had the strongest positive effect while soil pH had a negative effect on the two enzyme activity indices. In addition, total phosphorous content had a positive effect on TEI and GME in orchard soils, whereas alkali-hydrolyzable nitrogen and available potassium contents, respectively, had negative and positive effects on these two enzyme indices in cropland soils. The results indicate that land use changes strongly affect soil enzyme activities in agricultural land, where TEI provides a sensitive biological indicator for soil quality.
Dispersion and Cluster Scales in the Ocean
NASA Astrophysics Data System (ADS)
Kirwan, A. D., Jr.; Chang, H.; Huntley, H.; Carlson, D. F.; Mensa, J. A.; Poje, A. C.; Fox-Kemper, B.
2017-12-01
Ocean flow space scales range from centimeters to thousands of kilometers. Because of their large Reynolds number these flows are considered turbulent. However, because of rotation and stratification constraints they do not conform to classical turbulence scaling theory. Mesoscale and large-scale motions are well described by geostrophic or "2D turbulence" theory, however extending this theory to submesoscales has proved to be problematic. One obvious reason is the difficulty in obtaining reliable data over many orders of magnitude of spatial scales in an ocean environment. The goal of this presentation is to provide a preliminary synopsis of two recent experiments that overcame these obstacles. The first experiment, the Grand LAgrangian Deployment (GLAD) was conducted during July 2012 in the eastern half of the Gulf of Mexico. Here approximately 300 GPS-tracked drifters were deployed with the primary goal to determine whether the relative dispersion of an initially densely clustered array was driven by processes acting at local pair separation scales or by straining imposed by mesoscale motions. The second experiment was a component of the LAgrangian Submesoscale Experiment (LASER) conducted during the winter of 2016. Here thousands of bamboo plates were tracked optically from an Aerostat. Together these two deployments provided an unprecedented data set on dispersion and clustering processes from 1 to 106 meter scales. Calculations of statistics such as two point separations, structure functions, and scale dependent relative diffusivities showed: inverse energy cascade as expected for scales above 10 km, a forward energy cascade at scales below 10 km with a possible energy input at Langmuir circulation scales. We also find evidence from structure function calculations for surface flow convergence at scales less than 10 km that account for material clustering at the ocean surface.
Descriptive epidemiology of typhoid fever during an epidemic in Harare, Zimbabwe, 2012.
Polonsky, Jonathan A; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J
2014-01-01
Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range.
Descriptive Epidemiology of Typhoid Fever during an Epidemic in Harare, Zimbabwe, 2012
Polonsky, Jonathan A.; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J.
2014-01-01
Background Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. Methods A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. Principal Findings We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. Conclusions This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range. PMID:25486292
Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen
2008-07-29
This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.
Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen
2008-01-01
This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946
Wolfram, Phillip J.; Ringler, Todd D.; Maltrud, Mathew E.; ...
2015-08-01
Isopycnal diffusivity due to stirring by mesoscale eddies in an idealized, wind-forced, eddying, midlatitude ocean basin is computed using Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT). Simulation is performed via LIGHT within the Model for Prediction across Scales Ocean (MPAS-O). Simulations are performed at 4-, 8-, 16-, and 32-km resolution, where the first Rossby radius of deformation (RRD) is approximately 30 km. Scalar and tensor diffusivities are estimated at each resolution based on 30 ensemble members using particle cluster statistics. Each ensemble member is composed of 303 665 particles distributed across five potential density surfaces. Diffusivity dependence upon modelmore » resolution, velocity spatial scale, and buoyancy surface is quantified and compared with mixing length theory. The spatial structure of diffusivity ranges over approximately two orders of magnitude with values of O(10 5) m 2 s –1 in the region of western boundary current separation to O(10 3) m 2 s –1 in the eastern region of the basin. Dominant mixing occurs at scales twice the size of the first RRD. Model resolution at scales finer than the RRD is necessary to obtain sufficient model fidelity at scales between one and four RRD to accurately represent mixing. Mixing length scaling with eddy kinetic energy and the Lagrangian time scale yield mixing efficiencies that typically range between 0.4 and 0.8. In conclusion, a reduced mixing length in the eastern region of the domain relative to the west suggests there are different mixing regimes outside the baroclinic jet region.« less
NASA Astrophysics Data System (ADS)
Heine, Thomas R. P.; Moldwin, Mark B.; Zou, Shasha
2017-03-01
Kilometer-scale density irregularities in the ionosphere can cause ionospheric scintillation—a phenomenon that degrades space-based navigation and communication signals. During strong geomagnetic storms, the midlatitude ionosphere is primed to produce these ˜1-10 km small-scale irregularities along the steep gradients between midlatitude storm enhanced density (SED) plumes and the adjacent low-density trough. The length scales of irregularities on the order of 1-10 km are determined from a combination of spatial, temporal, and frequency analyses using single-station ground-based Global Positioning System total electron content (TEC) combined with radar plasma velocity measurements. Kilometer-scale irregularities are detected along the boundaries of the SED plume and depleted density trough during the 17 March 2015 geomagnetic storm, but not equatorward of the plume or within the plume itself. Analysis using the fast Fourier transform of high-pass filtered slant TEC suggests that the kilometer-scale irregularities formed near the poleward gradients of SED plumes can have similar intensity and length scales to those typically found in the aurora but are shown to be distinct phenomena in spacecraft electron precipitation measurements.
Fine-scale genetic response to landscape change in a gliding mammal.
Goldingay, Ross L; Harrisson, Katherine A; Taylor, Andrea C; Ball, Tina M; Sharpe, David J; Taylor, Brendan D
2013-01-01
Understanding how populations respond to habitat loss is central to conserving biodiversity. Population genetic approaches enable the identification of the symptoms of population disruption in advance of population collapse. However, the spatio-temporal scales at which population disruption occurs are still too poorly known to effectively conserve biodiversity in the face of human-induced landscape change. We employed microsatellite analysis to examine genetic structure and diversity over small spatial (mostly 1-50 km) and temporal scales (20-50 years) in the squirrel glider (Petaurus norfolcensis), a gliding mammal that is commonly subjected to a loss of habitat connectivity. We identified genetically differentiated local populations over distances as little as 3 km and within 30 years of landscape change. Genetically isolated local populations experienced the loss of genetic diversity, and significantly increased mean relatedness, which suggests increased inbreeding. Where tree cover remained, genetic differentiation was less evident. This pattern was repeated in two landscapes located 750 km apart. These results lend support to other recent studies that suggest the loss of habitat connectivity can produce fine-scale population genetic change in a range of taxa. This gives rise to the prediction that many other vertebrates will experience similar genetic changes. Our results suggest the future collapse of local populations of this gliding mammal is likely unless habitat connectivity is maintained or restored. Landscape management must occur on a fine-scale to avert the erosion of biodiversity.
NASA Technical Reports Server (NTRS)
Chao, Benjamin F.; Boy, J. P.
2003-01-01
With the advances of measurements, modern space geodesy has become a new type of remote sensing for the Earth dynamics, especially for mass transports in the geophysical fluids on large spatial scales. A case in point is the space gravity mission GRACE (Gravity Recovery And Climate Experiment) which has been in orbit collecting gravity data since early 2002. The data promise to be able to detect changes of water mass equivalent to sub-cm thickness on spatial scale of several hundred km every month or so. China s Three-Gorge Reservoir has already started the process of water impoundment in phases. By 2009,40 km3 of water will be stored behind one of the world s highest dams and spanning a section of middle Yangtze River about 600 km in length. For the GRACE observations, the Three-Gorge Reservoir would represent a geophysical controlled experiment , one that offers a unique opportunity to do detailed geophysical studies. -- Assuming a complete documentation of the water level and history of the water impoundment process and aided with a continual monitoring of the lithospheric loading response (such as in area gravity and deformation), one has at hand basically a classical forwardinverse modeling problem of surface loading, where the input and certain output are known. The invisible portion of the impounded water, i.e. underground storage, poses either added values as an observable or a complication as an unknown to be modeled. Wang (2000) has studied the possible loading effects on a local scale; we here aim for larger spatial scales upwards from several hundred km, with emphasis on the time-variable gravity signals that can be detected by GRACE and follow-on missions. Results using the Green s function approach on the PREM elastic Earth model indicate the geoid height variations reaching several millimeters on wavelengths of about a thousand kilometers. The corresponding vertical deformations have amplitude of a few centimeters. In terms of long-wavelength spherical harmonics, the induced geoid height variations are very close to the accuracy of GRACE- recoverable gravity field, while the low-degree (2 to 5) harmonics should be detectable. With a large regional time-variable gravity signal, the Three-Gorge experiment can serve as a useful calibration/verification for GRACE (including the elastic loading effects), and future gravity missions (especially for visco-elastic yielding as well as underground water variations).
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2013-08-01
Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.
Synoptic eddy-resolving Ocean Surveys over the Slope of the Chukchi Sea 2016 and 2017
NASA Astrophysics Data System (ADS)
Muenchow, A.; Elmer, C.; Badiey, M.; Eickmeier, J.; Ryan, P. A.
2017-12-01
Mild weather and warm waters kept the outer continental shelf of the Chukchi Sea ice-free in 2016 when we conducted ocean surveys as part of the Canada Basin Acoustic Propagation Experiment (CANAPE). We used standard CTD and ADCP profiling systems aboard R/V Sikuliaq to describe ocean density and velocity fields at 3 km scales across and 6 km scales along the slope. Our survey covers 800 km2between the 100-m and 400-m isobaths and resolves the internal Rossby radius of deformation which represents the dominant spatial (or eddy) scale for a density-stratified ocean. Our early November 2016 data revealed Bering Sea Summer Waters with temperatures exceeding 1.0 C at 80-m depth near the 200-m isobath. Three-dimensional distribution of this water and associated density gradients suggests a current to the east. The flow is likely unstable, we speculate, because it spawns eddy-like features that we will describe. We will test this hypothesis with ocean current shear estimated from vessel-mounted ADCP profiles. A similar survey is planned for October 2017, when USCGC Healy will re-visit the area to recover ocean moorings deployed prior to the 2016 surveys.
L-band HIgh Spatial Resolution Soil Moisture Mapping using SMALL UnManned Aerial Systems
NASA Astrophysics Data System (ADS)
Dai, E.; Venkitasubramony, A.; Gasiewski, A. J.; Stachura, M.; Elston, J. S.; Walter, B.; Lankford, D.; Corey, C.
2017-12-01
Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provided new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. However, there exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters. Compared with other methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site and Yuma Colorado Irrigation Research Foundation (IRF) site in 2015 and 2016, respectively, using LDCR Revision A and Tempest sUAS. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. LDCR Revision B has been built and integrated into SuperSwift sUAS and additional field experiments will be performed at IRF in 2017. In Revision B the IF signal is sampled at 80 MS/s to enable digital correlation and RFI mitigation capabilities, in addition to analog correlation. [1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C-Band Microwave Soil Moisture Retrieval During CLASIC 2007," Proc. IGARSS, 2008. [2] Robock, A., S. Steele-Dunne, J. Basara, W. Crow, and M. Moghaddam M, "In Situ Network and Scaling," SMAP Algorithm and Cal/Val Workshop, 2009. [3] Walker, A., "Airborne Microwave Radiometer Measurements During CanEx-SM10," Second SMAP Cal/Val Workshop, 2011.
NASA Astrophysics Data System (ADS)
Ko, A.; Mascaro, G.; Vivoni, E. R.
2017-12-01
Hyper-resolution (< 1 km) hydrological modeling is expected to support a range of studies related to the terrestrial water cycle. A critical need for increasing the utility of hyper-resolution modeling is the availability of meteorological forcings and land surface characteristics at high spatial resolution. Unfortunately, in many areas these datasets are only available at coarse (> 10 km) scales. In this study, we address some of the challenges by applying a parallel version of the Triangulated Irregular Network (TIN)-based Real Time Integrated Basin Simulator (tRIBS) to the Rio Sonora Basin (RSB) in northwest Mexico. The RSB is a large, semiarid watershed ( 21,000 km2) characterized by complex topography and a strong seasonality in vegetation conditions, due to the North American monsoon. We conducted simulations at an average spatial resolution of 88 m over a decadal (2004-2013) period using spatially-distributed forcings from remotely-sensed and reanalysis products. Meteorological forcings were derived from the North American Land Data Assimilation System (NLDAS) at the original resolution of 12 km and were downscaled at 1 km with techniques accounting for terrain effects. Two grids of soil properties were created from different sources, including: (i) CONABIO (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad) at 6 km resolution; and (ii) ISRIC (International Soil Reference Information Centre) at 250 m. Time-varying vegetation parameters were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) composite products. The model was first calibrated and validated through distributed soil moisture data from a network of 20 soil moisture stations during the monsoon season. Next, hydrologic simulations were conducted with five different combinations of coarse and downscaled forcings and soil properties. Outputs in the different configurations were then compared with independent observations of soil moisture, and with estimates of land surface temperature (1 km, daily) and evapotranspiration (1 km, monthly) from MODIS. This study is expected to support the community involved in hyper-resolution hydrologic modeling by identifying the crucial factors that, if available at higher resolution, lead to the largest improvement of the simulation prognostic capability.
Propagation of low energy solar electrons
NASA Technical Reports Server (NTRS)
Anderson, K. A.; Mcfadden, J. P.; Lin, R. P.
1981-01-01
Two events are reported in which 2-10 keV electrons of solar energy have undergone significant adiabatic mirroring and pitch angle scattering in large scale magnetic structures in the interplanetary medium within a distance of about 0.5 AU from the earth. Electrons of 3 keV, typical of the energies measured, have a speed of about one-tenth of the speed of light, so that their travel time from the sun at 0 deg pitch angle would be about 100 minutes. Their cyclotron radius is about 20 km for a pitch angle of 30 deg, and a field of magnitude of 5 nT, and the cyclotron period is about 7.1 milliseconds. The electrons are scattered by spatial variations in the interplanetary magnetic field. When the spatial variations are convected past a stationary spacecraft by a 500 km/sec solar wind, they are seen as temporal fluctuations at a frequency of about 3 Hz.
Gravity waves generated by a tropical cyclone during the STEP tropical field program - A case study
NASA Technical Reports Server (NTRS)
Pfister, L.; Chan, K. R.; Bui, T. P.; Bowen, S.; Legg, M.; Gary, B.; Kelly, K.; Proffitt, M.; Starr, W.
1993-01-01
Overflights of a tropical cyclone during the Australian winter monsoon field experiment of the Stratosphere-Troposphere Exchange Project (STEP) show the presence of two mesoscale phenomena: a vertically propagating gravity wave with a horizontal wavelength of about 110 km and a feature with a horizontal scale comparable to that of the cyclone's entire cloud shield. The larger feature is fairly steady, though its physical interpretation is ambiguous. The 110-km gravity wave is transient, having maximum amplitude early in the flight and decreasing in amplitude thereafter. Its scale is comparable to that of 100-to 150-km-diameter cells of low satellite brightness temperatures within the overall cyclone cloud shield; these cells have lifetimes of 4.5 to 6 hrs. These cells correspond to regions of enhanced convection, higher cloud altitude, and upwardly displaced potential temperature surfaces. The temporal and spatial distribution of meteorological variables associated with the 110-km gravity wave can be simulated by a slowly moving transient forcing at the anvil top having an amplitude of 400-600 m, a lifetime of 4.5-6 hrs, and a size comparable to the cells of low brightness temperature.
NASA Astrophysics Data System (ADS)
Essa, Salem M.; Loughland, R.; Khogali, Mohamed E.
2005-10-01
AL Sammalyah Island is considered an important protected area in Abu Dhabi Emirate. The island has witnessed high rates of change in land use in the past few years starting from the early 1990s. Change detection analysis is conducted to monitor rate and spatial distribution of change occurring on the island. A three-phase research project has been implemented, an integrated Geographic Information System (GIS) database for the Island is the focus; the current phase main objective was to assess rate and spatial distribution of the change on the island using multi-date large scale aerial photos. Results of the current study demonstrated that total vegetation cover extent has increased from 3.742 km2 in 1994 to 5.101 km2 in 2005, an increase of 36.3% between 1994 and 2005. The study also showed that this increase in vegetation extent is mostly attributed to the increase in mangrove planted areas with an increase from 2.256 km2 in 1994 to 3.568 km2 in 2005, an increase of 58.2% in ten years. Remote sensing and GIS have been successfully used to quantify change extent, distribution and trajectories of change. The next step will be to complete the GIS database for AL Sammalyah Island.
Klett, Katherine J.C.; Torgersen, Christian E.; Henning, Julie A.; Murray, Christopher J.
2013-01-01
We investigated the spawning patterns of Chinook Salmon Oncorhynchus tshawytscha on the lower Cowlitz River, Washington, using a unique set of fine- and coarse-scale temporal and spatial data collected during biweekly aerial surveys conducted in 1991–2009 (500 m to 28 km resolution) and 2008–2009 (100–500 m resolution). Redd locations were mapped from a helicopter during 2008 and 2009 with a hand-held GPS synchronized with in-flight audio recordings. We examined spatial patterns of Chinook Salmon redd reoccupation among and within years in relation to segment-scale geomorphic features. Chinook Salmon spawned in the same sections each year with little variation among years. On a coarse scale, 5 years (1993, 1998, 2000, 2002, and 2009) were compared for reoccupation. Redd locations were highly correlated among years. Comparisons on a fine scale (500 m) between 2008 and 2009 also revealed a high degree of consistency among redd locations. On a finer temporal scale, we observed that Chinook Salmon spawned in the same sections during the first and last week. Redds were clustered in both 2008 and 2009. Regression analysis with a generalized linear model at the 500-m scale indicated that river kilometer and channel bifurcation were positively associated with redd density, whereas sinuosity was negatively associated with redd density. Collecting data on specific redd locations with a GPS during aerial surveys was logistically feasible and cost effective and greatly enhanced the spatial precision of Chinook Salmon spawning surveys.
Comparison of C5 and C6 Aqua-MODIS Dark Target Aerosol Validation
NASA Technical Reports Server (NTRS)
Munchak, Leigh A.; Levy, Robert C.; Mattoo, Shana
2014-01-01
We compare C5 and C6 validation to compare the C6 10 km aerosol product against the well validated and trusted aerosol product on global and regional scales. Only the 10 km aerosol product is evaluated in this study, validation of the new C6 3 km aerosol product still needs to be performed. Not all of the time series has processed yet for C5 or C6, and the years processed for the 2 products is not exactly the same (this work is preliminary!). To reduce the impact of outlier observations, MODIS is spatially averaged within 27.5 km of the AERONET site, and AERONET is temporatally averaged within 30 minutes of the MODIS overpass time. Only high quality (QA = 3 over land, QA greater than 0 over ocean) pixels are included in the mean.
Discontinuities in stream nutrient uptake below lakes in mountain drainage networks
Arp, C.D.; Baker, M.A.
2007-01-01
In many watersheds, lakes and streams are hydrologically linked in spatial patterns that influence material transport and retention. We hypothesized that lakes affect stream nutrient cycling via modifications to stream hydrogeomorphology, source-waters, and biological communities. We tested this hypothesis in a lake district of the Sawtooth Mountains, Idaho. Uptake of NO3- and PO4-3 was compared among 25 reaches representing the following landscape positions: lake inlets and outlets, reaches >1-km downstream from lakes, and reference reaches with no nearby lakes. We quantified landscape-scale hydrographic and reach-scale hydrogeomorphic, source-water, and biological variables to characterize these landscape positions and analyze relationships to nutrient uptake. Nitrate uptake was undetectable at most lake outlets, whereas PO4-3 uptake was higher at outlets as compared to reference and lake inlet reaches. Patterns in nutrient demand farther downstream were similar to lake outlets with a gradual shift toward reference-reach functionality. Nitrate uptake was most correlated to sediment mobility and channel morphology, whereas PO 4-3 uptake was most correlated to source-water characteristics. The best integrated predictor of these patterns in nutrient demand was % contributing area (the proportion of watershed area not routing through a lake). We estimate that NO3- and PO 4-3 demand returned to 50% of pre-lake conditions within 1-4-km downstream of a small headwater lake and resetting of nutrient demand was slower downstream of a larger lake set lower in a watershed. Full resetting of these nutrient cycling processes was not reached within 20-km downstream, indicating that lakes can alter stream ecosystem functioning at large spatial scales throughout mountain watersheds. ?? 2007, by the American Society of Limnology and Oceanography, Inc.
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.
NASA Astrophysics Data System (ADS)
Kort, E. A.; Gvakharia, A.; Smith, M. L.; Conley, S.; Frauhammer, K.
2017-12-01
Nitrous Oxide (N2O) is a crucial atmospheric trace gas that drives 21st century stratospheric ozone depletion and substantively impacts climate. Anthropogenic emissions drive the global imbalance and annual growth of N2O, and the dominant anthropogenic source is fertilizer production and application, both of which have large uncertainties. In this presentation we will discuss the FEAST campaign, a study designed to demonstrate new approaches to quantify N2O emissions from fertilizer production and usage with aircraft measurements. In the FEAST campaign we deployed new instrumentation along with experienced flight sensors onboard the Scientific Aviation Mooney aircraft to make 40 hours of continuous 1Hz measurements of N2O, CO2, CO, H2O, CH4, O3, T, and winds. The Mississippi River Valley provided an optimal target as this location includes significant fertilizer production facilities as well as large cropland areas (dominated by corn, soy, rice, and cotton) with substantive fertilizer application. By leveraging our payload and unique airborne capabilities we directly observe and quantify N2O emissions from individual fertilizer production facilities (as well as CO2 and CH4 emissions from these same facilities). We are also able to quantify N2O fluxes from large cropland areas ( 100's km) employing a mass balance approach, a first for N2O, and will show results highlighting differences between crop types and amounts of applied fertilizer. The ability to quantify fluxes of croplands at 100km scale enables new understanding of processes controlling emissions at spatial scales that has eluded prior studies that either rely on extrapolation of small (flux chamber, towers), or work on 1,000+ km spatial scales (regional-global inversions from atmospheric measurements).
Baker, Edward; Christophe Hémond,; Anne Briais,; Marcia Maia,; Scheirer, Daniel S.; Sharon L. Walker,; Tingting Wang,; Yongshun John Chen,
2014-01-01
Multiple geological processes affect the distribution of hydrothermal venting along a mid-ocean ridge. Deciphering the role of a specific process is often frustrated by simultaneous changes in other influences. Here we take advantage of the almost constant spreading rate (65–71 mm/yr) along 2500 km of the Southeast Indian Ridge (SEIR) between 77°E and 99°E to examine the spatial density of hydrothermal venting relative to regional and segment-scale changes in the apparent magmatic budget. We use 227 vertical profiles of light backscatter and (on 41 profiles) oxidation-reduction potential along 27 first and second-order ridge segments on and adjacent to the Amsterdam-St. Paul (ASP) Plateau to map ph, the fraction of casts detecting a plume. At the regional scale, venting on the five segments crossing the magma-thickened hot spot plateau is almost entirely suppressed (ph = 0.02). Conversely, the combined ph (0.34) from all other segments follows the global trend of ph versus spreading rate. Off the ASP Plateau, multisegment trends in ph track trends in the regional axial depth, high where regional depth increases and low where it decreases. At the individual segment scale, a robust correlation between ph and cross-axis inflation for first-order segments shows that different magmatic budgets among first-order segments are expressed as different levels of hydrothermal spatial density. This correlation is absent among second-order segments. Eighty-five percent of the plumes occur in eight clusters totaling ∼350 km. We hypothesize that these clusters are a minimum estimate of the length of axial melt lenses underlying this section of the SEIR.
NASA Astrophysics Data System (ADS)
Schmalz, Britta; Kiesel, Jens; Kruse, Marion; Pfannerstill, Matthias; Sheludkov, Artyom; Khoroshavin, Vitaliy; Veshkurseva, Tatyana; Müller, Felix; Fohrer, Nicola
2015-04-01
For discussing and planning sustainable land management of river basins, stakeholders need suitable information on spatio-temporal patterns of hydrological components and ecosystem services. The ecosystem services concept, i.e., services provided by ecosystems that contribute to human welfare benefits, contributes comprehensive information for sustainable river management. This study shows an approach to use ecohydrological modelling results for quantifying and assessing water-related ecosystem services in three lowland river basins in Western Siberia, a region which is of global significance in terms of carbon sequestration, agricultural production and biodiversity preservation. Using the ecohydrological model SWAT, the three basins Pyschma (16762 km²), Vagai (3348 km²) and Loktinka (373 km²) were modelled following a gradient from the landscape units taiga, pre-taiga to forest steppe. For a correct representation of the Siberian lowland hydrology, the consideration of snow melt and retention of surface runoff as well as the implementation of a second groundwater aquifer was of great importance. Good to satisfying model performances were obtained for the extreme hydrological conditions. The simulated SWAT output variables of different hydrological processes were used as indicators for the two regulating services water flow and erosion regulation. The model results were translated into a relative ecosystem service valuation scale. The resulting ecosystem service maps show different spatial and seasonal patterns. Although the high resolution modelling results are averaged out within the aggregated relative valuation scale, seasonal differences can be depicted: during snowmelt, low relevant regulation can be determined, especially for water flow regulation, but a very high relevant regulation was calculated for the vegetation period during summer and for the winter period. The SWAT model serves as a suitable quantification method for the assessment of water-related ecosystem services on different spatial scales and ecoregions of the Western Siberian lowlands.
NASA Astrophysics Data System (ADS)
Baker, Edward T.; Hémond, Christophe; Briais, Anne; Maia, Marcia; Scheirer, Daniel S.; Walker, Sharon L.; Wang, Tingting; Chen, Yongshun John
2014-08-01
Multiple geological processes affect the distribution of hydrothermal venting along a mid-ocean ridge. Deciphering the role of a specific process is often frustrated by simultaneous changes in other influences. Here we take advantage of the almost constant spreading rate (65-71 mm/yr) along 2500 km of the Southeast Indian Ridge (SEIR) between 77°E and 99°E to examine the spatial density of hydrothermal venting relative to regional and segment-scale changes in the apparent magmatic budget. We use 227 vertical profiles of light backscatter and (on 41 profiles) oxidation-reduction potential along 27 first and second-order ridge segments on and adjacent to the Amsterdam-St. Paul (ASP) Plateau to map ph, the fraction of casts detecting a plume. At the regional scale, venting on the five segments crossing the magma-thickened hot spot plateau is almost entirely suppressed (ph = 0.02). Conversely, the combined ph (0.34) from all other segments follows the global trend of ph versus spreading rate. Off the ASP Plateau, multisegment trends in ph track trends in the regional axial depth, high where regional depth increases and low where it decreases. At the individual segment scale, a robust correlation between ph and cross-axis inflation for first-order segments shows that different magmatic budgets among first-order segments are expressed as different levels of hydrothermal spatial density. This correlation is absent among second-order segments. Eighty-five percent of the plumes occur in eight clusters totaling ˜350 km. We hypothesize that these clusters are a minimum estimate of the length of axial melt lenses underlying this section of the SEIR.
Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality
NASA Technical Reports Server (NTRS)
Levy, Robert C.; Remer, Lorraine A.; Kahn, Ralph A.; Chu, D. Allen; Mattoo, Shana; Holben, Brent N.; Schafer, Joel S.
2011-01-01
The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.
Hartwell Welsh; Garth Hodgson
2010-01-01
We investigated the aquatic and riparian herpetofauna in a 789 km² river catchment in northwest California to examine competing theories of biotic community structuring in catchment stream networks. Research in fluvial geomorphology has resulted in multi-scale models of dynamic processes that cyclically create, maintain, and destroy environments in stream...
Severe wind and fire regimes in northern forests: historical variability at the regional scale
Lisa A. Schulte; David J. Mladenoff
2005-01-01
Within the northern Great Lakes region, mesoscale (10s to 100s of km2) forest patterning is driven by disturbance dynamics. Using original Public Land Survey (PLS) records in northern Wisconsin, USA, we study spatial patterns of wind and fire disturbances during the pre-Euroamerican settlement period (ca. 1850). Our goals were: (1) to...
The validation process for a moderate resolution leaf area index (LAI) product (i.e., MODIS) involves the creation of a high spatial resolution LAI reference map (Lai-RM), which when scaled to the moderate LAI resolution (i.e., >1 km) allows for comparison and analysis with this ...
NASA Astrophysics Data System (ADS)
Martin, Adrian P.; Lévy, Marina; van Gennip, Simon; Pardo, Silvia; Srokosz, Meric; Allen, John; Painter, Stuart C.; Pidcock, Roz
2015-09-01
Numerous observations demonstrate that considerable spatial variability exists in components of the marine planktonic ecosystem at the mesoscale and submesoscale (100 km-1 km). The causes and consequences of physical processes at these scales ("eddy advection") influencing biogeochemistry have received much attention. Less studied, the nonlinear nature of most ecological and biogeochemical interactions means that such spatial variability has consequences for regional estimates of processes including primary production and grazing, independent of the physical processes. This effect has been termed "eddy reactions." Models remain our most powerful tools for extrapolating hypotheses for biogeochemistry to global scales and to permit future projections. The spatial resolution of most climate and global biogeochemical models means that processes at the mesoscale and submesoscale are poorly resolved. Modeling work has previously suggested that the neglected eddy reactions may be almost as large as the mean field estimates in some cases. This study seeks to quantify the relative size of eddy and mean reactions observationally, using in situ and satellite data. For primary production, grazing, and zooplankton mortality the eddy reactions are between 7% and 15% of the mean reactions. These should be regarded as preliminary estimates to encourage further observational estimates and not taken as a justification for ignoring eddy reactions. Compared to modeling estimates, there are inconsistencies in the relative magnitude of eddy reactions and in correlations which are a major control on their magnitude. One possibility is that models exhibit much stronger spatial correlations than are found in reality, effectively amplifying the magnitude of eddy reactions.
Spatial and temporal resolution effects on urban catchments with different imperviousness degrees
NASA Astrophysics Data System (ADS)
Cristiano, Elena; ten Veldhuis, Marie-Claire; van de Giesen, Nick C.
2015-04-01
One of the main problems in urban hydrological analysis is to measure the rainfall at urban scale with high resolution and use these measurements to model urban runoff processes to predict flows and reduce flood risk. With the aim of building a semi-distribute hydrological sewer model for an urban catchment, high resolution rainfall data are required as input. In this study, the sensitivity of hydrological response to high resolution precipitation data for hydrodynamic models at urban scale is evaluated with different combinations of spatial and temporal resolutions. The aim is to study sensitivity in relation to catchment characteristics, especially drainage area size, imperviousness degree and hydraulic properties such as special structures (weirs, pumping stations). Rainfall data of nine storms are considered with 4 different spatial resolutions (3000m, 1000m, 500m and 100m) combined with 4 different temporal resolutions (10min, 5min, 3min and 1min). The dual polarimetric X-band weather radar, located in the Cabauw Experimental Site for Atmospheric Research (CESAR) provided the high resolution rainfall data of these rainfall events, used to improve the sewer model. The effects of spatial-temporal rainfall input resolution on response is studied in three Districts of Rotterdam (NL): Kralingen, Spaanse Polder and Centrum district. These catchments have different average drainage area size (from 2km2 to 7km2), and different general characteristics. Centrum district and Kralingen are, indeed, more various and include residential and commercial areas, big green areas and a small industrial area, while Spaanse Polder is a industrial area, densely urbanized, and presents a high percentage of imperviousness.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matsui, Hitoshi; Koike, Makoto; Kondo, Yutaka
Weather Research and Forecasting (WRF)-chem model calculations were conducted to study aerosol optical properties around Beijing, China, during the Campaign of Air Quality Research in Beijing and Surrounding Region 2006 (CAREBeijing-2006) period. In this paper, we interpret aerosol optical properties in terms of aerosol mass concentrations and their chemical compositions by linking model calculations with measurements. In general, model calculations reproduced observed features of spatial and temporal variations of various surface and column aerosol optical parameters in and around Beijing. Spatial and temporal variations of aerosol absorption, scattering, and extinction coefficient corresponded well to those of elemental carbon (primary aerosol),more » sulfate (secondary aerosol), and the total aerosol mass concentration, respectively. These results show that spatial and temporal variations of the absorption coefficient are controlled by local emissions (within 100 km around Beijing during the preceding 24 h), while those of the scattering coefficient are controlled by regional-scale emissions (within 500 km around Beijing during the preceding 3 days) under synoptic-scale meteorological conditions, as discussed in our previous study of aerosol mass concentration. Vertical profiles of aerosol extinction revealed that the contribution of secondary aerosols and their water uptake increased with altitude within the planetary boundary layer, leading to a considerable increase in column aerosol optical depth (AOD) around Beijing. These effects are the main factors causing differences in regional and temporal variations between particulate matter (PM) mass concentration at the surface and column AOD over a wide region in the northern part of the Great North China Plain.« less
Nevers, M.B.; Whitman, R.L.
2008-01-01
To understand the fate and movement of Escherichia coli in beach water, numerous modeling studies have been undertaken including mechanistic predictions of currents and plumes and empirical modeling based on hydrometeorological variables. Most approaches are limited in scope by nearshore currents or physical obstacles and data limitations; few examine the issue from a larger spatial scale. Given the similarities between variables typically included in these models, we attempted to take a broader view of E. coli fluctuations by simultaneously examining twelve beaches along 35 km of Indiana's Lake Michigan coastline that includes five point-source outfalls. The beaches had similar E. coli fluctuations, and a best-fit empirical model included two variables: wave height and an interactive term comprised of wind direction and creek turbidity. Individual beach R2 was 0.32-0.50. Data training-set results were comparable to validation results (R2 = 0.48). Amount of variation explained by the model was similar to previous reports for individual beaches. By extending the modeling approach to include more coastline distance, broader-scale spatial and temporal changes in bacteria concentrations and the influencing factors can be characterized. ?? 2008 American Chemical Society.
The [N II] Kinematics of R Aquarii
NASA Technical Reports Server (NTRS)
Hollis, J. M.; Vogel, S. N.; VanBuren, D.; Strong, J. P.; Lyon, R. G.; Dorband, J. E.
1998-01-01
We report a kinematic study of the symbiotic star system R Aqr derived from [N H]lambda 6584 emission observations with a Fabry-Perot imaging spectrometer. The [N II] spatial structure of the R Aqr jet, first observed circa 1977, and surrounding hourglass-shaped nebulosity, due to an explosion approximately 660 years ago, are derived from 41 velocity planes spaced at approximately 12 km/s intervals. Fabry-Perot imagery shows the elliptical nebulosity comprising the waist of the hourglass shell is consistent with a circular ring expanding radially at 55 km/s as seen at an inclination angle, i approximately 70 deg. Fabry-Perot imagery shows the two-sided R Aqr jet is collimated flow in opposite directions. The intensity-velocity structure of the strong NE jet component is shown in contrast to the amorphous SW jet component. We offer a idealized schematic model for the R Aqr jet motion which results in a small-scale helical structure forming around a larger-scale helical path. The implications of such a jet model are discussed. We present a movie showing a side-by-side comparison of the spatial structure of the model and the data as a function of the 41 velocity planes.
Karsten, Minette; van Vuuren, Bettine Jansen; Barnaud, Adeline; Terblanche, John S
2013-01-01
The invasive Mediterranean fruit fly (medfly), Ceratitis capitata, is one of the major agricultural and economical pests globally. Understanding invasion risk and mitigation of medfly in agricultural landscapes requires knowledge of its population structure and dispersal patterns. Here, estimates of dispersal ability are provided in medfly from South Africa at three spatial scales using molecular approaches. Individuals were genotyped at 11 polymorphic microsatellite loci and a subset of individuals were also sequenced for the mitochondrial cytochrome oxidase subunit I gene. Our results show that South African medfly populations are generally characterized by high levels of genetic diversity and limited population differentiation at all spatial scales. This suggests high levels of gene flow among sampling locations. However, natural dispersal in C. capitata has been shown to rarely exceed 10 km. Therefore, documented levels of high gene flow in the present study, even between distant populations (>1600 km), are likely the result of human-mediated dispersal or at least some form of long-distance jump dispersal. These findings may have broad applicability to other global fruit production areas and have significant implications for ongoing pest management practices, such as the sterile insect technique.
Multiple neutral density measurements in the lower thermosphere with cold-cathode ionization gauges
NASA Astrophysics Data System (ADS)
Lehmacher, G. A.; Gaulden, T. M.; Larsen, M. F.; Craven, J. D.
2013-01-01
Cold-cathode ionization gauges were used for rocket-borne measurements of total neutral density and temperature in the aurorally forced lower thermosphere between 90 and 200 km. A commercial gauge was adapted as a low-cost instrument with a spherical antechamber for measurements in molecular flow conditions. Three roll-stabilized payloads on different trajectories each carried two instruments for measurements near the ram flow direction along the respective upleg and downleg segments of a flight path, and six density profiles were obtained within a period of 22 min covering spatial separations up to 200 km. The density profiles were integrated below 125 km to yield temperatures. The mean temperature structure was similar for all six profiles with two mesopause minima near 110 and 101 km, however, for the downleg profiles, the upper minimum was warmer and the lower minimum was colder by 20-30 K indicating significant variability over horizontal scales of 100-200 km. The upper temperature minimum coincided with maximum horizontal winds speeds, exceeding 170 m/s.
Response of Moist Convection to Multi-scale Surface Flux Heterogeneity
NASA Astrophysics Data System (ADS)
Kang, S. L.; Ryu, J. H.
2015-12-01
We investigate response of moist convection to multi-scale feature of the spatial variation of surface sensible heat fluxes (SHF) in the afternoon evolution of the convective boundary layer (CBL), utilizing a mesoscale-domain large eddy simulation (LES) model. The multi-scale surface heterogeneity feature is analytically created as a function of the spectral slope in the wavelength range from a few tens of km to a few hundreds of m in the spectrum of surface SHF on a log-log scale. The response of moist convection to the κ-3 - slope (where κ is wavenumber) surface SHF field is compared with that to the κ-2 - slope surface, which has a relatively weak mesoscale feature, and the homogeneous κ0 - slope surface. Given the surface energy balance with a spatially uniform available energy, the prescribed SHF has a 180° phase lag with the latent heat flux (LHF) in a horizontal domain of (several tens of km)2. Thus, warmer (cooler) surface is relatively dry (moist). For all the cases, the same observation-based sounding is prescribed for the initial condition. For all the κ-3 - slope surface heterogeneity cases, early non-precipitating shallow clouds further develop into precipitating deep thunderstorms. But for all the κ-2 - slope cases, only shallow clouds develop. We compare the vertical profiles of domain-averaged fluxes and variances, and the contribution of the mesoscale and turbulence contributions to the fluxes and variances, between the κ-3 versus κ-2 slope cases. Also the cross-scale processes are investigated.
NASA Astrophysics Data System (ADS)
Nakano, Masuo; Wada, Akiyoshi; Sawada, Masahiro; Yoshimura, Hiromasa; Onishi, Ryo; Kawahara, Shintaro; Sasaki, Wataru; Nasuno, Tomoe; Yamaguchi, Munehiko; Iriguchi, Takeshi; Sugi, Masato; Takeuchi, Yoshiaki
2017-03-01
Recent advances in high-performance computers facilitate operational numerical weather prediction by global hydrostatic atmospheric models with horizontal resolutions of ˜ 10 km. Given further advances in such computers and the fact that the hydrostatic balance approximation becomes invalid for spatial scales < 10 km, the development of global nonhydrostatic models with high accuracy is urgently required. The Global 7 km mesh nonhydrostatic Model Intercomparison Project for improving TYphoon forecast (TYMIP-G7) is designed to understand and statistically quantify the advantages of high-resolution nonhydrostatic global atmospheric models to improve tropical cyclone (TC) prediction. A total of 137 sets of 5-day simulations using three next-generation nonhydrostatic global models with horizontal resolutions of 7 km and a conventional hydrostatic global model with a horizontal resolution of 20 km were run on the Earth Simulator. The three 7 km mesh nonhydrostatic models are the nonhydrostatic global spectral atmospheric Double Fourier Series Model (DFSM), the Multi-Scale Simulator for the Geoenvironment (MSSG) and the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). The 20 km mesh hydrostatic model is the operational Global Spectral Model (GSM) of the Japan Meteorological Agency. Compared with the 20 km mesh GSM, the 7 km mesh models reduce systematic errors in the TC track, intensity and wind radii predictions. The benefits of the multi-model ensemble method were confirmed for the 7 km mesh nonhydrostatic global models. While the three 7 km mesh models reproduce the typical axisymmetric mean inner-core structure, including the primary and secondary circulations, the simulated TC structures and their intensities in each case are very different for each model. In addition, the simulated track is not consistently better than that of the 20 km mesh GSM. These results suggest that the development of more sophisticated initialization techniques and model physics is needed to further improve the TC prediction.
NASA Astrophysics Data System (ADS)
Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos
2014-05-01
One of the key point in the develop of the MOTEDAS dataset (see Poster 1 MOTEDAS) in the framework of the HIDROCAES Project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is the reference series for which no generalized metadata exist. In this poster we present an analysis of spatial variability of monthly minimum and maximum temperatures in the conterminous land of Spain (Iberian Peninsula, IP), by using the Correlation Decay Distance function (CDD), with the aim of evaluating, at sub-regional level, the optimal threshold distance between neighbouring stations for producing the set of reference series used in the quality control (see MOTEDAS Poster 1) and the reconstruction (see MOREDAS Poster 3). The CDD analysis for Tmax and Tmin was performed calculating a correlation matrix at monthly scale between 1981-2010 among monthly mean values of maximum (Tmax) and minimum (Tmin) temperature series (with at least 90% of data), free of anomalous data and homogenized (see MOTEDAS Poster 1), obtained from AEMEt archives (National Spanish Meteorological Agency). Monthly anomalies (difference between data and mean 1981-2010) were used to prevent the dominant effect of annual cycle in the CDD annual estimation. For each station, and time scale, the common variance r2 (using the square of Pearson's correlation coefficient) was calculated between all neighbouring temperature series and the relation between r2 and distance was modelled according to the following equation (1): Log (r2ij) = b*°dij (1) being Log(rij2) the common variance between target (i) and neighbouring series (j), dij the distance between them and b the slope of the ordinary least-squares linear regression model applied taking into account only the surrounding stations within a starting radius of 50 km and with a minimum of 5 stations required. Finally, monthly, seasonal and annual CDD values were interpolated using the Ordinary Kriging with a spherical variogram over conterminous land of Spain, and converted on a regular 10 km2 grid (resolution similar to the mean distance between stations) to map the results. In the conterminous land of Spain the distance at which couples of stations have a common variance in temperature (both maximum Tmax, and minimum Tmin) above the selected threshold (50%, r Pearson ~0.70) on average does not exceed 400 km, with relevant spatial and temporal differences. The spatial distribution of the CDD shows a clear coastland-to-inland gradient at annual, seasonal and monthly scale, with highest spatial variability along the coastland areas and lower variability inland. The highest spatial variability coincide particularly with coastland areas surrounded by mountain chains and suggests that the orography is one of the most driving factor causing higher interstation variability. Moreover, there are some differences between the behaviour of Tmax and Tmin, being Tmin spatially more homogeneous than Tmax, but its lower CDD values indicate that night-time temperature is more variable than diurnal one. The results suggest that in general local factors affects the spatial variability of monthly Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for Tmin respect to Tmax. The results suggest that in general local factors affects the spatial variability of Tmin more than Tmax and then higher network density would be necessary to capture the higher spatial variability highlighted for minimum temperature respect to maximum temperature. A conservative distance for reference series could be evaluated in 200 km, that we propose for continental land of Spain and use in the development of MOTEDAS.
NASA Astrophysics Data System (ADS)
Pawson, S.; Nielsen, J.; Ott, L. E.; Darmenov, A.; Putman, W.
2015-12-01
Model-data fusion approaches, such as global inverse modeling for surface flux estimation, have traditionally been performed at spatial resolutions of several tens to a few hundreds of kilometers. Use of such coarse scales presents a fundamental limitation in reconciling the modeled field with both the atmospheric observations and the distribution of surface emissions and uptake. Emissions typically occur on small scales, including point sources (e.g. power plants, forest fires) or with inhomegeneous structure. Biological uptake can have spatial variations related to complex, diverse vegetation, etc. Atmospheric observations of CO2 are either surface based, providing information at a single point, or space based with a finite-sized footprint. For instance, GOSAT and OCO-2 have footprint sizes of around 10km and proposed active sensors (such as ASCENDS) will likely have even finer footprints. One important aspect of reconciling models to measurements is the representativeness of the observation for the model field, and this depends on the generally unknown spatio-temporal variations of the CO2 field around the measurement location and time. This work presents an assessment of the global spatio-temporal variations of the CO2 field using the "7km GEOS-5 Nature Run" (7km-G5NR), which includes CO2 emissions and uptake mapped to the finest possible resolution. Results are shown for surface CO2 concentrations, total-column CO2, and separate upper and lower tropospheric columns. Spatial variability is shown to be largest in regions with strong point sources and at night in regions with complex terrain, especially where biological processes dominate the local CO2 fluxes, where the day-night differences are also most marked. The spatio-temporal variations are strongest for surface concentrations and for lower tropospheric CO2. While these results are largely anticipated, these high resolution simulations provide quantitative estimates of the global nature of spatio-temporal CO2 variability. Implications for characterizing representativeness of passive CO2 observations will be discussed. Differences between daytime and nighttime structures will be considered in light of active CO2 sensors. Finally, some possible limitations of the model will be highlighted, using some global 3-km simulations.
TES/Aura L3 Atmospheric Temperatures Daily V4 (TL3ATD)
Atmospheric Science Data Center
2018-05-09
... Platform: TES Aura L1B Nadir/Limb Spatial Coverage: 5.3 x 8.5 km nadir 37 x 23 km limb Spatial ... 0.5 x 5 km nadir 2.3 x 23 km limb Temporal Coverage: 08/22/2004 - present Temporal Resolution: ...
The scientific targets of the SCOPE mission
NASA Astrophysics Data System (ADS)
Fujimoto, M.; Saito, Y.; Tsuda, Y.; Shinohara, I.; Kojima, H.
Future Japanese magnetospheric mission "SCOPE" is now under study (planned to be launched in 2012). The main purpose of this mission is to investigate the dynamic behaviors of plasmas in the Earth's magnetosphere from the view-point of cross-scale coupling. Dynamical collisionless space plasma phenomena, be they large scale as a whole, are chracterized by coupling over various time and spatial scales. The best example would be the magnetic reconnection process, which is a large scale energy conversion process but has a small key region at the heart of its engine. Inside the key region, electron scale dynamics plays the key role in liberating the frozen-in constraint, by which reconnection is allowed to proceed. The SCOPE mission is composed of one large mother satellite and four small daughter satellites. The mother spacecraft will be equiped with the electron detector that has 10 msec time resolution so that scales down to the electron's will be resolved. Three of the four daughter satellites surround the mother satellite 3-dimensionally with the mutual distances between several km and several thousand km, which are varied during the mission. Plasma measurements on these spacecrafts will have 1 sec resolution and will provide information on meso-scale plasma structure. The fourth daughter satellite stays near the mother satellite with the distance less than 100km. By correlation between the two plasma wave instruments on the daughter and the mother spacecrafts, propagation of the waves and the information on the electron scale dynamics will be obtained. By this strategy, both meso- and micro-scale information on dynamics are obtained, that will enable us to investigate the physics of the space plasma from the cross-scale coupling point of view.
NASA Astrophysics Data System (ADS)
Poje, Andrew C.; Ã-zgökmen, Tamay M.; Bogucki, Darek J.; Kirwan, A. D.
2017-02-01
Using two-point velocity and position data from the near-simultaneous release of O(100) GPS-tracked surface drifters in the northern Gulf of Mexico, we examine the applicability of classical turbulent scaling laws to upper ocean velocity fields. The dataset allows direct estimates of both velocity structure functions and the temporal evolution of the distribution of particle pair separations. On 100 m-10 km spatial scales, and time scales of order 1-10 days, all metrics of the observed surface fluctuations are consistent with standard Kolmogorov turbulence theory in an energy cascade inertial-range regime. The sign of the third-order structure function is negative and proportional to the separation distance for scales ≲10 km where local, fluctuating Rossby numbers are found to be larger than 0.1. The scale-independent energy dissipation rate, or downscale spectral flux, estimated from Kolmogorov's 4/5th law in this regime closely matches nearby microscale dissipation measurements in the near-surface. In contrast, similar statistics derived from a like-sized set of synthetic drifters advected by purely geostrophic altimetric AVISO data agree well with Kolmogorov-Kraichnan scaling for 2D turbulence in the forward enstrophy cascade range.
NASA Astrophysics Data System (ADS)
Lin, Shian-Jiann; Harris, Lucas; Chen, Jan-Huey; Zhao, Ming
2014-05-01
A multi-scale High-Resolution Atmosphere Model (HiRAM) is being developed at NOAA/Geophysical Fluid Dynamics Laboratory. The model's dynamical framework is the non-hydrostatic extension of the vertically Lagrangian finite-volume dynamical core (Lin 2004, Monthly Wea. Rev.) constructed on a stretchable (via Schmidt transformation) cubed-sphere grid. Physical parametrizations originally designed for IPCC-type climate predictions are in the process of being modified and made more "scale-aware", in an effort to make the model suitable for multi-scale weather-climate applications, with horizontal resolution ranging from 1 km (near the target high-resolution region) to as low as 400 km (near the antipodal point). One of the main goals of this development is to enable simulation of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously thought impossible. We will present preliminary results, covering a very wide spectrum of temporal-spatial scales, ranging from simulation of tornado genesis (hours), Madden-Julian Oscillations (intra-seasonal), topical cyclones (seasonal), to Quasi Biennial Oscillations (intra-decadal), using the same global multi-scale modeling system.
Spatial resolution requirements for urban land cover mapping from space
NASA Technical Reports Server (NTRS)
Todd, William J.; Wrigley, Robert C.
1986-01-01
Very low resolution (VLR) satellite data (Advanced Very High Resolution Radiometer, DMSP Operational Linescan System), low resolution (LR) data (Landsat MSS), medium resolution (MR) data (Landsat TM), and high resolution (HR) satellite data (Spot HRV, Large Format Camera) were evaluated and compared for interpretability at differing spatial resolutions. VLR data (500 m - 1.0 km) is useful for Level 1 (urban/rural distinction) mapping at 1:1,000,000 scale. Feature tone/color is utilized to distinguish generalized urban land cover using LR data (80 m) for 1:250,000 scale mapping. Advancing to MR data (30 m) and 1:100,000 scale mapping, confidence in land cover mapping is greatly increased, owing to the element of texture/pattern which is now evident in the imagery. Shape and shadow contribute to detailed Level II/III urban land use mapping possible if the interpreter can use HR (10-15 m) satellite data; mapping scales can be 1:25,000 - 1:50,000.
Upwelling Scales off the Coast of Peru: Comparison of Observation and Model
NASA Astrophysics Data System (ADS)
Vazquez, J.; Chin, T. M.; Armstrong, E. M.
2014-12-01
Upwelling regions of the world's oceans are home to some of the most productive fisheries. Yet these coastal areas provide unique challenges for remote sensing from satellite platforms because of both their proximity to land (radar interference) and typically small horizontal scales (< 50km) of upwelling processes. Comparisons are performed on the gradient of sea surface temperature (SST) fields derived from multiple sources: 1) the 0.25 degree resolution National Climatic Data Center (NCDC) Optimally Interpolated AVHRR+in-situ or AVHRR_OI, data set. 2) the 1km resolution Multi-scale Ultra-high Resolution (MUR) gridded SST data set, 3) the 0.25 degree resolution SST derived from the WindSat microwave sensor, 4) a 2km version of the Estimating the Circulation and Climate of the Ocean Model (HECCO2). Temporal and spatial correlations between HECCO2 and MUR, as well as between HECCO2 and NCDC, are examined through the dominant singular vectors (eigenmodes) of the covariance matrix for each pair of data sets. In both cases the first mode of covariability accounts for over 90% of the total variance. A simple technique based on SST gradients is then applied to the first mode to determine the upwelling scales based on HECCO2, MUR, and NCDC. Longitudinal sections at 8S, 20S, and 30S indicate that the upwelling scale decreases between 8S and 20S. At 20S the first mode of covariability between MUR and HECCO2 indicate an upwelling scale between 25 and 50km. Results are consistent when compared with chlorophyll-a data from MODIS-Aqua. Such upwelling scales are not seen in the WindSat data and reduced in the NCDC data. A reduction of the upwelling scale by a factor 0.2 between 8S and 20S is consistent with a dependence on the Coriolis parameter. A major conclusion of the work is that magnitudes of SST gradient and upwelling scales derived from MUR are consistent with those of the HECCO2 for the test period of October-November 2011. Additionally, it is shown that to resolve upwelling scales near the coast high resolution infrared data must be used in the analysis. Microwave derived SSTs, such as those from WindSat are of limited value when upwelling scales are less then 50km.
Critiquing ';pore connectivity' as basis for in situ flow in geothermal systems
NASA Astrophysics Data System (ADS)
Kenedi, C. L.; Leary, P.; Malin, P.
2013-12-01
Geothermal system in situ flow systematics derived from detailed examination of grain-scale structures, fabrics, mineral alteration, and pore connectivity may be extremely misleading if/when extrapolated to reservoir-scale flow structure. In oil/gas field clastic reservoir operations, it is standard to assume that small scale studies of flow fabric - notably the Kozeny-Carman and Archie's Law treatments at the grain-scale and well-log/well-bore sampling of formations/reservoirs at the cm-m scale - are adequate to define the reservoir-scale flow properties. In the case of clastic reservoirs, however, a wide range of reservoir-scale data wholly discredits this extrapolation: Well-log data show that grain-scale fracture density fluctuation power scales inversely with spatial frequency k, S(k) ~ 1/k^β, 1.0 < β < 1.2, 1cycle/km < k < 1cycle/cm; the scaling is a ';universal' feature of well-logs (neutron porosity, sonic velocity, chemical abundance, mass density, resistivity, in many forms of clastic rock and instances of shale bodies, for both horizontal and vertical wells). Grain-scale fracture density correlates with in situ porosity; spatial fluctuations of porosity φ in well-core correlate with spatial fluctuations in the logarithm of well-core permeability, δφ ~ δlog(κ) with typical correlation coefficient ~ 85%; a similar relation is observed in consolidating sediments/clays, indicating a generic coupling between fluid pressure and solid deformation at pore sites. In situ macroscopic flow systems are lognormally distributed according to κ ~ κ0 exp(α(φ-φ0)), α >>1 an empirical parameter for degree of in situ fracture connectivity; the lognormal distribution applies to well-productivities in US oil fields and NZ geothermal fields, ';frack productivity' in oil/gas shale body reservoirs, ore grade distributions, and trace element abundances. Although presently available evidence for these properties in geothermal reservoirs is limited, there are indications that geothermal system flow essentially obeys the same ';universal' in situ flow rules as does clastic rock: Well-log data from Los Azufres, MX, show power-law scaling S(k) ~ 1/k^β, 1.2 < β < 1.4, for spatial frequency range 2cycles/km to 0.5cycle/m; higher β-values are likely due to the relatively fresh nature of geothermal systems; Well-core at Bulalo (PH) and Ohaaki (NZ) show statistically significant spatial correlation, δφ ~ δlog(κ) Well productivity at Ohaaki/Ngawha (NZ) and in geothermal systems elsewhere are lognormally distributed; K/Th/U abundances lognormally distributed in Los Azufres well-logs We therefore caution that small-scale evidence for in situ flow fabric in geothermal systems that is interpreted in terms of ';pore connectivity' may in fact not reflect how small-scale chemical processes are integrated into a large-scale geothermal flow structure. Rather such small scale studies should (perhaps) be considered in term of the above flow rules. These flow rules are easily incorporated into standard flow simulation codes, in particular the OPM = Open Porous Media open-source industry-standard flow code. Geochemical transport data relevant to geothermal systems can thus be expected to be well modeled by OPM or equivalent (e.g., INL/LANL) codes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.
Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration's (NASA) Terra satellite to scale up AmeriFlux NEE measurements to themore » continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE well (r = 0.73, p < 0.001). We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xiao, Jingfeng; Zhuang, Qianlai; Baldocchi, Dennis D.
Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely-sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board NASA's Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS andmore » AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a regression tree approach. The predictive model was trained and validated using NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE reasonably well at the site level. We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day period in 2005 using spatially-explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets for large areas.« less
Rodrigues, Bruno Leite; Carvalho-Costa, Luís Fernando; Pinto, Israel de Souza; Rebêlo, José Manuel Macário
2018-03-17
Sand fly (Diptera: Psychodidae) taxonomy is complex and time-consuming, which hampers epidemiological efforts directed toward controlling leishmaniasis in endemic regions such as northeastern Brazil. Here, we used a fragment of the mitochondrial cytochrome c oxidase I (COI) gene to identify sand fly species in Maranhão State (northeastern Brazil) and to assess cryptic diversity occurring at different spatial scales. For this, we obtained 148 COI sequences of 15 sand fly species (10 genera) from Maranhão (fine spatial scale), and joined them to COI sequences from other Brazilian localities (distant about 2,000 km from Maranhão, broad spatial scale) available in GenBank. We revealed cases of cryptic diversity in sand flies both at fine (Lutzomyia longipalpis (Lutz and Neiva) and Evandromyia termitophila (Martins, Falcão and Silva)) and broad spatial scales (Migonemyia migonei (França), Pressatia choti (Floch and Abonnenc), Psychodopygus davisi (Root), Sciopemyia sordellii (Shannon and Del Ponte), and Bichromomyia flaviscutellata (Mangabeira)). We argue that in the case of Bi. flaviscutellata, the cryptic diversity is associated with a putative new species. Cases in which DNA taxonomy was not as effective as morphological identification possibly involved recent speciation and/or introgressive hybridization, highlighting the need for integrative approaches to identify some sand fly species. Finally, we provide the first barcode sequences for four species (Brumptomyia avellari (Costa Lima), Evandromyia infraspinosa (Mangabeira), Evandromyia evandroi (Costa Lima and Antunes), and Psychodopygus complexus (Mangabeira)), which will be useful for further molecular identification of neotropical species.
NASA Astrophysics Data System (ADS)
Carnell, E. J.; Misselbrook, T. H.; Dore, A. J.; Sutton, M. A.; Dragosits, U.
2017-09-01
The effects of atmospheric nitrogen (N) deposition are evident in terrestrial ecosystems worldwide, with eutrophication and acidification leading to significant changes in species composition. Substantial reductions in N deposition from nitrogen oxides emissions have been achieved in recent decades. By contrast, ammonia (NH3) emissions from agriculture have not decreased substantially and are typically highly spatially variable, making efficient mitigation challenging. One solution is to target NH3 mitigation measures spatially in source landscapes to maximize the benefits for nature conservation. The paper develops an approach to link national scale data and detailed local data to help identify suitable measures for spatial targeting of local sources near designated Special Areas of Conservation (SACs). The methodology combines high-resolution national data on emissions, deposition and source attribution with local data on agricultural management and site conditions. Application of the methodology for the full set of 240 SACs in England found that agriculture contributes ∼45 % of total N deposition. Activities associated with cattle farming represented 54 % of agricultural NH3 emissions within 2 km of the SACs, making them a major contributor to local N deposition, followed by mineral fertiliser application (21 %). Incorporation of local information on agricultural management practices at seven example SACs provided the means to correct outcomes compared with national-scale emission factors. The outcomes show how national scale datasets can provide information on N deposition threats at landscape to national scales, while local-scale information helps to understand the feasibility of mitigation measures, including the impact of detailed spatial targeting on N deposition rates to designated sites.
Hierarchical Population Genetic Structure in a Direct Developing Antarctic Marine Invertebrate
Hoffman, Joseph I.; Clarke, Andrew; Clark, Melody S.; Peck, Lloyd S.
2013-01-01
Understanding the relationship between life-history variation and population structure in marine invertebrates is not straightforward. This is particularly true of polar species due to the difficulty of obtaining samples and a paucity of genomic resources from which to develop nuclear genetic markers. Such knowledge, however, is essential for understanding how different taxa may respond to climate change in the most rapidly warming regions of the planet. We therefore used over two hundred polymorphic Amplified Fragment Length Polymorphisms (AFLPs) to explore population connectivity at three hierachical spatial scales in the direct developing Antarctic topshell Margarella antarctica. To previously published data from five populations spanning a 1500 km transect along the length of the Western Antarctic Peninsula, we added new AFLP data for four populations separated by up to 6 km within Ryder Bay, Adelaide Island. Overall, we found a nonlinear isolation-by-distance pattern, suggestive of weaker population structure within Ryder Bay than is present over larger spatial scales. Nevertheless, significantly positive F st values were obtained in all but two of ten pairwise population comparisons within the bay following Bonferroni correction for multiple tests. This is in contrast to a previous study of the broadcast spawner Nacella concinna that found no significant genetic differences among several of the same sites. By implication, the topshell's direct-developing lifestyle may constrain its ability to disperse even over relatively small geographic scales. PMID:23691125
NASA Astrophysics Data System (ADS)
Pelland, Noel A.; Eriksen, Charles C.; Cronin, Meghan F.
2016-09-01
A Seaglider autonomous underwater vehicle augmented the Ocean Station Papa (OSP; 50°N, 145°W) surface mooring, measuring spatial structure on scales relevant to the monthly evolution of the moored time series. During each of three missions from June 2008 to January 2010, a Seaglider made biweekly 50 km × 50 km surveys in a bowtie-shaped survey track. Horizontal temperature and salinity gradients measured by these surveys were an order of magnitude stronger than climatological values and sometimes of opposite sign. Geostrophically inferred circulation was corroborated by moored acoustic Doppler current profiler measurements and AVISO satellite altimetry estimates of surface currents, confirming that glider surveys accurately resolved monthly scale mesoscale spatial structure. In contrast to climatological North Pacific Current circulation, upper-ocean flow was modestly northward during the first half of the 18 month survey period, and weakly westward during its latter half, with Rossby number O>(0.01>). This change in circulation coincided with a shift from cool and fresh to warm, saline, oxygen-rich water in the upper-ocean halocline, and an increase in vertical fine structure there and in the lower pycnocline. The anomalous flow and abrupt water mass transition were due to the slow growth of an anticyclonic meander within the North Pacific Current with radius comparable to the scale of the survey pattern, originating to the southeast of OSP.
Scale dependency of regional climate modeling of current and future climate extremes in Germany
NASA Astrophysics Data System (ADS)
Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver
2017-11-01
A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.
Ionospheric scintillation by a random phase screen Spectral approach
NASA Technical Reports Server (NTRS)
Rufenach, C. L.
1975-01-01
The theory developed by Briggs and Parkin, given in terms of an anisotropic gaussian correlation function, is extended to a spectral description specified as a continuous function of spatial wavenumber with an intrinsic outer scale as would be expected from a turbulent medium. Two spectral forms were selected for comparison: (1) a power-law variation in wavenumber with a constant three-dimensional index equal to 4, and (2) Gaussian spectral variation. The results are applied to the F-region ionosphere with an outer-scale wavenumber of 2 per km (approximately equal to the Fresnel wavenumber) for the power-law variation, and 0.2 per km for the Gaussian spectral variation. The power-law form with a small outer-scale wavenumber is consistent with recent F-region in-situ measurements, whereas the gaussian form is mathematically convenient and, hence, mostly used in the previous developments before the recent in-situ measurements. Some comparison with microwave scintillation in equatorial areas is made.
Ubiquitous and Continuous Propagating Disturbances in the Solar Corona
NASA Astrophysics Data System (ADS)
Morgan, Huw; Hutton, Joseph
2018-02-01
A new processing method applied to Atmospheric Imaging Assembly/Solar Dynamic Observatory observations reveals continuous propagating faint motions throughout the corona. The amplitudes are small, typically 2% of the background intensity. An hour’s data are processed from four AIA channels for a region near disk center, and the motions are characterized using an optical flow method. The motions trace the underlying large-scale magnetic field. The motion vector field describes large-scale coherent regions that tend to converge at narrow corridors. Large-scale vortices can also be seen. The hotter channels have larger-scale regions of coherent motion compared to the cooler channels, interpreted as the typical length of magnetic loops at different heights. Regions of low mean and high time variance in velocity are where the dominant motion component is along the line of sight as a result of a largely vertical magnetic field. The mean apparent magnitude of the optical velocities are a few tens of km s‑1, with different distributions in different channels. Over time, the velocities vary smoothly between a few km s‑1 to 100 km s‑1 or higher, varying on timescales of minutes. A clear bias of a few km s‑1 toward positive x-velocities is due to solar rotation and may be used as calibration in future work. All regions of the low corona thus experience a continuous stream of propagating disturbances at the limit of both spatial resolution and signal level. The method provides a powerful new diagnostic tool for tracing the magnetic field, and to probe motions at sub-pixel scales, with important implications for models of heating and of the magnetic field.
Assessing the Spatial Scale Effect of Anthropogenic Factors on Species Distribution
Mangiacotti, Marco; Scali, Stefano; Sacchi, Roberto; Bassu, Lara; Nulchis, Valeria; Corti, Claudia
2013-01-01
Patch context is a way to describe the effect that the surroundings exert on a landscape patch. Despite anthropogenic context alteration may affect species distributions by reducing the accessibility to suitable patches, species distribution modelling have rarely accounted for its effects explicitly. We propose a general framework to statistically detect the occurrence and the extent of such a factor, by combining presence-only data, spatial distribution models and information-theoretic model selection procedures. After having established the spatial resolution of the analysis on the basis of the species characteristics, a measure of anthropogenic alteration that can be quantified at increasing distance from each patch has to be defined. Then the distribution of the species is modelled under competing hypotheses: H0, assumes that the distribution is uninfluenced by the anthropogenic variables; H1, assumes the effect of alteration at the species scale (resolution); and H2, H3 … Hn add the effect of context alteration at increasing radii. Models are compared using the Akaike Information Criterion to establish the best hypothesis, and consequently the occurrence (if any) and the spatial scale of the anthropogenic effect. As a study case we analysed the distribution data of two insular lizards (one endemic and one naturalised) using four alternative hypotheses: no alteration (H0), alteration at the species scale (H1), alteration at two context scales (H2 and H3). H2 and H3 performed better than H0 and H1, highlighting the importance of context alteration. H2 performed better than H3, setting the spatial scale of the context at 1 km. The two species respond differently to context alteration, the introduced lizard being more tolerant than the endemic one. The proposed approach supplies reliably and interpretable results, uses easily available data on species distribution, and allows the assessing of the spatial scale at which human disturbance produces the heaviest effects. PMID:23825669
Spatial structure and scaling of macropores in hydrological process at small catchment scale
NASA Astrophysics Data System (ADS)
Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter
2013-04-01
During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video cameras and soil moisture monitoring equipment to obtain the initial data of overland flow occurrence and soil moisture state relationships.
Dependence of Snowmelt Simulations on Scaling of the Forcing Processes (Invited)
NASA Astrophysics Data System (ADS)
Winstral, A. H.; Marks, D. G.; Gurney, R. J.
2009-12-01
The spatial organization and scaling relationships of snow distribution in mountain environs is ultimately dependent on the controlling processes. These processes include interactions between weather, topography, vegetation, snow state, and seasonally-dependent radiation inputs. In large scale snow modeling it is vital to know these dependencies to obtain accurate predictions while reducing computational costs. This study examined the scaling characteristics of the forcing processes and the dependency of distributed snowmelt simulations to their scaling. A base model simulation characterized these processes with 10m resolution over a 14.0 km2 basin with an elevation range of 1474 - 2244 masl. Each of the major processes affecting snow accumulation and melt - precipitation, wind speed, solar radiation, thermal radiation, temperature, and vapor pressure - were independently degraded to 1 km resolution. Seasonal and event-specific results were analyzed. Results indicated that scale effects on melt vary by process and weather conditions. The dependence of melt simulations on the scaling of solar radiation fluxes also had a seasonal component. These process-based scaling characteristics should remain static through time as they are based on physical considerations. As such, these results not only provide guidance for current modeling efforts, but are also well suited to predicting how potential climate changes will affect the heterogeneity of mountain snow distributions.
Diagnostics of multi-fractality of magnetized plasma inside coronal holes and quiet sun areas
NASA Astrophysics Data System (ADS)
Abramenko, Valentyna
Turbulent and multi-fractal properties of magnetized plasma in solar Coronal Holes (CHs) and Quiet Sun (QS) photosphere were explored using high-resolution magnetograms measured with the New Solar Telescope (NST) at the Big Bear Solar Observatory (BBSO, USA), Hinode/SOT and SDO/HMI instruments. Distribution functions of size and magnetic flux measured for small-scale magnetic elements follow the log-normal law, which implies multi-fractal organization of the magnetic field and the absence of a unique power law for all scales. The magnetograms show multi-fractality in CHs on scales 400 - 10000 km, which becomes better pronounced as the spatial resolution of data improves. Photospheric granulation measured with NST exhibits multi-fractal properties on very small scales of 50 - 600 km. While multi-fractal nature of solar active regions is well known, newly established multi-fractality of weakest magnetic fields on the solar surface, i.e., in CHs and QS, leads us to a conclusion that the entire variety of solar magnetic fields is generated by a unique nonlinear dynamical process.
Interplanetary scintillation observations with the Cocoa Cross radio telescope
NASA Technical Reports Server (NTRS)
Cronyn, W. M.; Shawhan, S. D.; Erskine, F. T.; Huneke, A. H.; Mitchell, D. G.
1976-01-01
Physical and electrical parameters for the 34.3-MHz Cocoa Cross radio telescope are given. The telescope is dedicated to the determination of solar-wind characteristics in and out of the ecliptic plane through measurement of electron-density irregularity structure as determined from IPS (interplanetary scintillation) of natural radio sources. The collecting area (72,000 sq m), angular resolution (0.4 deg EW by 0.6 deg NS), and spatial extent (1.3 km EW by 0.8 km NS) make the telescope well suited for measurements of IPS index and frequency scale for hundreds of weak radio sources without serious confusion effects.
Deploying temporary networks for upscaling of sparse network stations
NASA Astrophysics Data System (ADS)
Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane
2016-10-01
Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.
The 1 km resolution global data set: needs of the International Geosphere Biosphere Programme
Townshend, J.R.G.; Justice, C.O.; Skole, D.; Malingreau, J.-P.; Cihlar, J.; Teillet, P.; Sadowski, F.; Ruttenberg, S.
1994-01-01
Examination of the scientific priorities for the International Geosphere Biosphere Programme (IGBP) reveals a requirement for global land data sets in several of its Core Projects. These data sets need to be at several space and time scales. Requirements are demonstrated for the regular acquisition of data at spatial resolutions of 1 km and finer and at high temporal frequencies. Global daily data at a resolution of approximately 1 km are sensed by the Advanced Very High Resolution Radiometer (AVHRR), but they have not been available in a single archive. It is proposed, that a global data set of the land surface is created from remotely sensed data from the AVHRR to support a number of IGBP's projects. This data set should have a spatial resolution of 1 km and should be generated at least once every 10 days for the entire globe. The minimum length of record should be a year, and ideally a system should be put in place which leads to the continuous acquisition of 1 km data to provide a base line data set prior to the Earth Observing System (EOS) towards the end of the decade. Because of the high cloud cover in many parts of the world, it is necessary to plan for the collection of data from every orbit. Substantial effort will be required in the preprocessing of the data set involving radiometric calibration, atmospheric correction, geometric correction and temporal compositing, to make it suitable for the extraction of information.
SMAP Soil Moisture Disaggregation using Land Surface Temperature and Vegetation Data
NASA Astrophysics Data System (ADS)
Fang, B.; Lakshmi, V.
2016-12-01
Soil moisture (SM) is a key parameter in agriculture, hydrology and ecology studies. The global SM retrievals have been providing by microwave remote sensing technology since late 1970s and many SM retrieval algorithms have been developed, calibrated and applied on satellite sensors such as AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System), AMSR-2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). Particularly, SMAP (Soil Moisture Active/Passive) satellite, which was developed by NASA, was launched in January 2015. SMAP provides soil moisture products of 9 km and 36 km spatial resolutions which are not capable for research and applications of finer scale. Toward this issue, this study applied a SM disaggregation algorithm to disaggregate SMAP passive microwave soil moisture 36 km product. This algorithm was developed based on the thermal inertial relationship between daily surface temperature variation and daily average soil moisture which is modulated by vegetation condition, by using remote sensing retrievals from AVHRR (Advanced Very High Resolution Radiometer, MODIS (Moderate Resolution Imaging Spectroradiometer), SPOT (Satellite Pour l'Observation de la Terre), as well as Land Surface Model (LSM) output from NLDAS (North American Land Data Assimilation System). The disaggregation model was built at 1/8o spatial resolution on monthly basis and was implemented to calculate and disaggregate SMAP 36 km SM retrievals to 1 km resolution in Oklahoma. The SM disaggregation results were also validated using MESONET (Mesoscale Network) and MICRONET (Microscale Network) ground SM measurements.
An Approach to Evaluate the Spatial Fidelity of Satellite-Derived Sea Surface Temperature Fields
NASA Astrophysics Data System (ADS)
Cornillon, P. C.; Wu, F.; Guan, L.; Boussidi, B.
2016-12-01
An approach to evaluate the spatial fidelity of satellite-derived SST fields for spatial scales in the range of one to a few tens of pixels is presented. The approach is based on spatial spectra of the SST fields in an oceanographically `quiet' region, the Sargasso Sea between the southern edge of the Gulf Stream and Bermuda. Spectra are relatively isotropic in this region, allowing for analysis of the spectra in along-scan and cross-scan directions for level 2 fields and in coordinate directions for level 3 and level 4 fields, and spectral energy levels tend to be low for the ocean, allowing for a diagnosis of the pixel-to-pixel noise levels in the associated spectra. The focus on the spatial fidelity of the derived fields is intended to fill a gap in the measure of the overall quality of satellite-derived SST fields. To date the primary measure of these data has been via the comparison of in situ buoy measurements with `match-ups' from the satellite-derived fields. Such measures provide for the accuracy of the retrievals but not of their spatial precision. The approach presented here addresses the latter. Spectra obtained in this region from the satellite-borne sensors are compared with those obtained from a thermal recorder on the container ship Oleander making weekly roundtrips between Port Elizabeth, NJ and Bermuda. To demonstrate the approach, it is applied to Level 2 VIIRS and AVHRR SST fields. The most accurate spectra for VIIRS fields are obtained for nighttime sections in the along-scan direction within 500 km of nadir. Along-track sections show signs of banding from the multiple detectors of the VIIRS instrument. By contrast AVHRR spectra show elevated energy at the submesoscale (<25km), likely due to instrument noise but poor cloud-screening may also contribute the spectral energy at these scales.
NASA Astrophysics Data System (ADS)
He, L.; Ivanov, V. Y.; Bohrer, G.; Maurer, K.; Vogel, C. S.; Moghaddam, M.
2011-12-01
Vegetation is heterogeneous at different scales, influencing spatially variable energy and water exchanges between land-surface and atmosphere. Current land surface parameterizations of large-scale models consider spatial variability at a scale of a few kilometers and treat vegetation cover as aggregated patches with uniform properties. However, the coupling mechanisms between fine-scale soil moisture, vegetation, and energy fluxes such as evapotranspiration are strongly nonlinear; the aggregation of surface variations may produce biased energy fluxes. This study aims to improve the understanding of the scale impact in atmosphere-biosphere-hydrosphere interactions, which affects predictive capabilities of land surface models. The study uses a high-resolution, physically-based ecohydrological model tRIBS + VEGGIE as a data integration tool to upscale the heterogeneity of canopy distribution resolved at a few meters to the watershed scale. The study was carried out for a spatially heterogeneous, temperate mixed forest environment of Northern Michigan located near the University of Michigan Biological Station (UMBS). Energy and soil water dynamics were simulated at the tree-canopy resolution in the horizontal plane for a small domain (~2 sq. km) located within a footprint of the AmeriFlux tower. A variety of observational data were used to constrain and confirm the model, including a 3-m profile continuous soil moisture dataset and energy flux data (measured at the AmeriFlux tower footprint). A scenario with a spatially uniform canopy, corresponding to the commonly used 'big-leaf' scheme in land surface parameterizations was used to infer the effects of coarse-scale averaging. To gain insights on how heterogeneous canopy and soil moisture interact and contribute to the domain-averaged transpiration, several scenarios of tree-scale leaf area and soil moisture spatial variability were designed. Specifically, for the same mean states, the scenarios of variability of canopy biomass account for the spatial distribution of photosynthesis (and thus the stomatal resistance), the aerodynamic and leaf boundary layer resistances as well as the differential radiation forcing due to tall tree exposure and lateral shading of short trees. The numerical experiments show that by transpiring spatially varying amounts of water, heterogeneous canopies adjust the spatial soil water state to the scaled inverse of the canopy biomass regardless of the initial moisture state. Such a spatial distribution can be further wiped out because of the differential water stress. The aggregation of canopy-scale atmosphere-biosphere-hydrosphere interactions demonstrates non-linear relationship between soil moisture and evapotranspiration, influencing domain-averaged energy fluxes.
Schultz, Arthur L.; Malcolm, Hamish A.; Bucher, Daniel J.; Linklater, Michelle; Smith, Stephen D. A.
2014-01-01
Where biological datasets are spatially limited, abiotic surrogates have been advocated to inform objective planning for Marine Protected Areas. However, this approach assumes close correlation between abiotic and biotic patterns. The Solitary Islands Marine Park, northern NSW, Australia, currently uses a habitat classification system (HCS) to assist with planning, but this is based only on data for reefs. We used Baited Remote Underwater Videos (BRUVs) to survey fish assemblages of unconsolidated substrata at different depths, distances from shore, and across an along-shore spatial scale of 10 s of km (2 transects) to examine how well the HCS works for this dominant habitat. We used multivariate regression modelling to examine the importance of these, and other environmental factors (backscatter intensity, fine-scale bathymetric variation and rugosity), in structuring fish assemblages. There were significant differences in fish assemblages across depths, distance from shore, and over the medium spatial scale of the study: together, these factors generated the optimum model in multivariate regression. However, marginal tests suggested that backscatter intensity, which itself is a surrogate for sediment type and hardness, might also influence fish assemblages and needs further investigation. Species richness was significantly different across all factors: however, total MaxN only differed significantly between locations. This study demonstrates that the pre-existing abiotic HCS only partially represents the range of fish assemblages of unconsolidated habitats in the region. PMID:24824998
High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies
NASA Technical Reports Server (NTRS)
Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.
2013-01-01
The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment for the daily variability in the AOD-PM(sub 2.5) relationship provides a means for obtaining spatially-resolved PM(sub 2.5) concentrations.
Fire history reconstruction in grassland ecosystems: amount of charcoal reflects local area burned
NASA Astrophysics Data System (ADS)
Leys, Bérangère; Brewer, Simon C.; McConaghy, Scott; Mueller, Joshua; McLauchlan, Kendra K.
2015-11-01
Fire is one of the most prevalent disturbances in the Earth system, and its past characteristics can be reconstructed using charcoal particles preserved in depositional environments. Although researchers know that fires produce charcoal particles, interpretation of the quantity or composition of charcoal particles in terms of fire source remains poorly understood. In this study, we used a unique four-year dataset of charcoal deposited in traps from a native tallgrass prairie in mid-North America to test which environmental factors were linked to charcoal measurements on three spatial scales. We investigated small and large charcoal particles commonly used as a proxy of fire activity at different spatial scales, and charcoal morphotypes representing different types of fuel. We found that small (125-250 μm) and large (250 μm-1 mm) particles of charcoal are well-correlated (Spearman correlation = 0.88) and likely reflect the same spatial scale of fire activity in a system with both herbaceous and woody fuels. There was no significant relationship between charcoal pieces and fire parameters <500 m from the traps. Moreover, local area burned (<5 km distance radius from traps) explained the total charcoal amount, and regional burning (200 km radius distance from traps) explained the ratio of non arboreal to total charcoal (NA/T ratio). Charcoal variables, including total charcoal count and NA/T ratio, did not correlate with other fire parameters, vegetation cover, landscape, or climate variables. Thus, in long-term studies that involve fire history reconstructions, total charcoal particles, even of a small size (125-250 μm), could be an indicator of local area burned. Further studies may determine relationships among amount of charcoal recorded, fire intensity, vegetation cover, and climatic parameters.
Remote sensing in support of high-resolution terrestrial carbon monitoring and modeling
NASA Astrophysics Data System (ADS)
Hurtt, G. C.; Zhao, M.; Dubayah, R.; Huang, C.; Swatantran, A.; ONeil-Dunne, J.; Johnson, K. D.; Birdsey, R.; Fisk, J.; Flanagan, S.; Sahajpal, R.; Huang, W.; Tang, H.; Armstrong, A. H.
2014-12-01
As part of its Phase 1 Carbon Monitoring System (CMS) activities, NASA initiated a Local-Scale Biomass Pilot study. The goals of the pilot study were to develop protocols for fusing high-resolution remotely sensed observations with field data, provide accurate validation test areas for the continental-scale biomass product, and demonstrate efficacy for prognostic terrestrial ecosystem modeling. In Phase 2, this effort was expanded to the state scale. Here, we present results of this activity focusing on the use of remote sensing in high-resolution ecosystem modeling. The Ecosystem Demography (ED) model was implemented at 90 m spatial resolution for the entire state of Maryland. We rasterized soil depth and soil texture data from SSURGO. For hourly meteorological data, we spatially interpolated 32-km 3-hourly NARR into 1-km hourly and further corrected them at monthly level using PRISM data. NLCD data were used to mask sand, seashore, and wetland. High-resolution 1 m forest/non-forest mapping was used to define forest fraction of 90 m cells. Three alternative strategies were evaluated for initialization of forest structure using high-resolution lidar, and the model was used to calculate statewide estimates of forest biomass, carbon sequestration potential, time to reach sequestration potential, and sensitivity to future forest growth and disturbance rates, all at 90 m resolution. To our knowledge, no dynamic ecosystem model has been run at such high spatial resolution over such large areas utilizing remote sensing and validated as extensively. There are over 3 million 90 m land cells in Maryland, greater than 43 times the ~73,000 half-degree cells in a state-of-the-art global land model.
NASA Astrophysics Data System (ADS)
Guilinger, J. J.; Crosby, B. T.
2017-12-01
Excessive suspended sediment in streams is one of the most common causes for industrial, ecological and recreational stream impairment in the US. Identifying the primary geomorphic or anthropogenic sources of sediment is a key step in the effective mitigation of impairment. This study seeks to identify sources of suspended sediment in an agriculturally impaired watershed, Marsh Creek, in southeast Idaho. We employ thirteen multi-parameter water quality sensors to simultaneously measure stage, turbidity, temperature and conductivity every 15 minutes over a full calendar year. Examined at both the event and annual scale, these data enable mass balance calculations for mainstem and tributary contributions. Revealed in this monitoring is an approximately eight-fold longitudinal increase in sediment flux over 74 km that is largely augmented by eroding mainstem banks in reaches with higher stream power in the lower 30 km, with less than 20% contributed from tributaries. Independent data confirming the bank source were acquired through cost-effective sediment fingerprinting using 15N and C:N signatures from potential soil endmembers. Additionally, Google Street View-type longitudinal imagery of banks was collected via a kayak survey to confirm the spatial extent and magnitude of bank erosion along Marsh Creek. These data converge on bank erosion as the primary source of fine sediment. Sediment load at various hierarchical temporal and spatial scales is impacted by in-stream storage and remobilization, especially over shorter timescales ranging from daily to seasonal periods. Once averaged over the annual scale, local, temporary in-channel storage is overcome and these data reveal source reaches that can be prioritized for restoration and mitigation projects.
David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Maosheng Zhao; Steve W. Running; Steven C. Wofsy; Shawn Urbanski; Allison L. Dunn; J.W. Munger
2003-01-01
The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using...
Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model
NASA Technical Reports Server (NTRS)
De Lannoy, Gabrielle J.M.; Reichle, Rolf H.; Houser, Paul R.; Arsenault, Kristi R.; Verhoest, Niko E.C.; Paulwels, Valentijn R.N.
2009-01-01
An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.
NASA Astrophysics Data System (ADS)
Sedlak, René; Hannawald, Patrick; Schmidt, Carsten; Wüst, Sabine; Bittner, Michael
2016-12-01
A new version of the Fast Airglow Imager (FAIM) for the detection of atmospheric waves in the OH airglow layer has been set up at the German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR) at Oberpfaffenhofen (48.09° N, 11.28° E), Germany. The spatial resolution of the instrument is 17 m pixel-1 in zenith direction with a field of view (FOV) of 11.1 km × 9.0 km at the OH layer height of ca. 87 km. Since November 2015, the system has been in operation in two different setups (zenith angles 46 and 0°) with a temporal resolution of 2.5 to 2.8 s. In a first case study we present observations of two small wave-like features that might be attributed to gravity wave instabilities. In order to spectrally analyse harmonic structures even on small spatial scales down to 550 m horizontal wavelength, we made use of the maximum entropy method (MEM) since this method exhibits an excellent wavelength resolution. MEM further allows analysing relatively short data series, which considerably helps to reduce problems such as stationarity of the underlying data series from a statistical point of view. We present an observation of the subsequent decay of well-organized wave fronts into eddies, which we tentatively interpret in terms of an indication for the onset of turbulence. Another remarkable event which demonstrates the technical capabilities of the instrument was observed during the night of 4-5 April 2016. It reveals the disintegration of a rather homogenous brightness variation into several filaments moving in different directions and with different speeds. It resembles the formation of a vortex with a horizontal axis of rotation likely related to a vertical wind shear. This case shows a notable similarity to what is expected from theoretical modelling of Kelvin-Helmholtz instabilities (KHIs). The comparatively high spatial resolution of the presented new version of the FAIM provides new insights into the structure of atmospheric wave instability and turbulent processes. Infrared imaging of wave dynamics on the sub-kilometre scale in the airglow layer supports the findings of theoretical simulations and modellings.
NASA Astrophysics Data System (ADS)
Ardhuin, Fabrice; Gille, Sarah; Menemenlis, Dimitris; Rocha, Cesar; Rascle, Nicolas; Gula, Jonathan; Chapron, Bertrand
2017-04-01
Tidal currents and large oceanic currents, such as the Agulhas, Gulf Stream and Kuroshio, are known to modify ocean wave properties, causing extreme sea states that are a hazard to navigation. Recent advances in the understanding and modeling capability of ocean currents at scales of 10 km or less have revealed the ubiquitous presence of fronts and filaments. Based on realistic numerical models, we show that these structures can be the main source of variability in significant wave heights at scales less than 200 km, including important variations at 10 km. This current-induced variability creates gradients in wave heights that were previously overlooked and are relevant for extreme wave heights and remote sensing. The spectrum of significant wave heights is found to be of the order of 70⟨Hs ⟩2/(g2⟨Tm0,-1⟩2) times the current spectrum, where ⟨Hs ⟩ is the spatially-averaged significant wave height, ⟨Tm0,-1⟩ is the average energy period, and g is the gravity acceleration. This small scale variability is consistent with Jason-3 and SARAL along-track variability. We will discuss how future satellite mission with wave spectrometers can help observe these wave-current interactions. CFOSAT is due for launch in 2018, and SKIM is a proposal for ESA Earth Explorer 9.
Exploring seascape genetics and kinship in the reef sponge Stylissa carteri in the Red Sea
Giles, Emily C; Saenz-Agudelo, Pablo; Hussey, Nigel E; Ravasi, Timothy; Berumen, Michael L
2015-01-01
A main goal of population geneticists is to study patterns of gene flow to gain a better understanding of the population structure in a given organism. To date most efforts have been focused on studying gene flow at either broad scales to identify barriers to gene flow and isolation by distance or at fine spatial scales in order to gain inferences regarding reproduction and local dispersal. Few studies have measured connectivity at multiple spatial scales and have utilized novel tools to test the influence of both environment and geography on shaping gene flow in an organism. Here a seascape genetics approach was used to gain insight regarding geographic and ecological barriers to gene flow of a common reef sponge, Stylissa carteri in the Red Sea. Furthermore, a small-scale (<1 km) analysis was also conducted to infer reproductive potential in this organism. At the broad scale, we found that sponge connectivity is not structured by geography alone, but rather, genetic isolation in the southern Red Sea correlates strongly with environmental heterogeneity. At the scale of a 50-m transect, spatial autocorrelation analyses and estimates of full-siblings revealed that there is no deviation from random mating. However, at slightly larger scales (100–200 m) encompassing multiple transects at a given site, a greater proportion of full-siblings was found within sites versus among sites in a given location suggesting that mating and/or dispersal are constrained to some extent at this spatial scale. This study adds to the growing body of literature suggesting that environmental and ecological variables play a major role in the genetic structure of marine invertebrate populations. PMID:26257865
Behavioral responses of wolves to roads: scale-dependent ambivalence
Nelson, Lindsey; Wabakken, Petter; Sand, Håkan; Liberg, Olof
2014-01-01
Throughout their recent recovery in several industrialized countries, large carnivores have had to cope with a changed landscape dominated by human infrastructure. Population growth depends on the ability of individuals to adapt to these changes by making use of new habitat features and at the same time to avoid increased risks of mortality associated with human infrastructure. We analyzed the summer movements of 19 GPS-collared resident wolves (Canis lupus L.) from 14 territories in Scandinavia in relation to roads. We used resource and step selection functions, including >12000 field-checked GPS-positions and 315 kill sites. Wolves displayed ambivalent responses to roads depending on the spatial scale, road type, time of day, behavioral state, and reproductive status. At the site scale (approximately 0.1 km2), they selected for roads when traveling, nearly doubling their travel speed. Breeding wolves moved the fastest. At the patch scale (10 km2), house density rather than road density was a significant negative predictor of wolf patch selection. At the home range scale (approximately 1000 km2), breeding wolves increased gravel road use with increasing road availability, although at a lower rate than expected. Wolves have adapted to use roads for ease of travel, but at the same time developed a cryptic behavior to avoid human encounters. This behavioral plasticity may have been important in allowing the successful recovery of wolf populations in industrialized countries. However, we emphasize the role of roads as a potential cause of increased human-caused mortality. PMID:25419085
Sea-ice deformation in a coupled ocean-sea-ice model and in satellite remote sensing data
NASA Astrophysics Data System (ADS)
Spreen, Gunnar; Kwok, Ron; Menemenlis, Dimitris; Nguyen, An T.
2017-07-01
A realistic representation of sea-ice deformation in models is important for accurate simulation of the sea-ice mass balance. Simulated sea-ice deformation from numerical simulations with 4.5, 9, and 18 km horizontal grid spacing and a viscous-plastic (VP) sea-ice rheology are compared with synthetic aperture radar (SAR) satellite observations (RGPS, RADARSAT Geophysical Processor System) for the time period 1996-2008. All three simulations can reproduce the large-scale ice deformation patterns, but small-scale sea-ice deformations and linear kinematic features (LKFs) are not adequately reproduced. The mean sea-ice total deformation rate is about 40 % lower in all model solutions than in the satellite observations, especially in the seasonal sea-ice zone. A decrease in model grid spacing, however, produces a higher density and more localized ice deformation features. The 4.5 km simulation produces some linear kinematic features, but not with the right frequency. The dependence on length scale and probability density functions (PDFs) of absolute divergence and shear for all three model solutions show a power-law scaling behavior similar to RGPS observations, contrary to what was found in some previous studies. Overall, the 4.5 km simulation produces the most realistic divergence, vorticity, and shear when compared with RGPS data. This study provides an evaluation of high and coarse-resolution viscous-plastic sea-ice simulations based on spatial distribution, time series, and power-law scaling metrics.
Behavioral responses of wolves to roads: scale-dependent ambivalence.
Zimmermann, Barbara; Nelson, Lindsey; Wabakken, Petter; Sand, Håkan; Liberg, Olof
2014-11-01
Throughout their recent recovery in several industrialized countries, large carnivores have had to cope with a changed landscape dominated by human infrastructure. Population growth depends on the ability of individuals to adapt to these changes by making use of new habitat features and at the same time to avoid increased risks of mortality associated with human infrastructure. We analyzed the summer movements of 19 GPS-collared resident wolves ( Canis lupus L.) from 14 territories in Scandinavia in relation to roads. We used resource and step selection functions, including >12000 field-checked GPS-positions and 315 kill sites. Wolves displayed ambivalent responses to roads depending on the spatial scale, road type, time of day, behavioral state, and reproductive status. At the site scale (approximately 0.1 km 2 ), they selected for roads when traveling, nearly doubling their travel speed. Breeding wolves moved the fastest. At the patch scale (10 km 2 ), house density rather than road density was a significant negative predictor of wolf patch selection. At the home range scale (approximately 1000 km 2 ), breeding wolves increased gravel road use with increasing road availability, although at a lower rate than expected. Wolves have adapted to use roads for ease of travel, but at the same time developed a cryptic behavior to avoid human encounters. This behavioral plasticity may have been important in allowing the successful recovery of wolf populations in industrialized countries. However, we emphasize the role of roads as a potential cause of increased human-caused mortality.
Fine-Scale Genetic Response to Landscape Change in a Gliding Mammal
Goldingay, Ross L.; Harrisson, Katherine A.; Taylor, Andrea C.; Ball, Tina M.; Sharpe, David J.; Taylor, Brendan D.
2013-01-01
Understanding how populations respond to habitat loss is central to conserving biodiversity. Population genetic approaches enable the identification of the symptoms of population disruption in advance of population collapse. However, the spatio-temporal scales at which population disruption occurs are still too poorly known to effectively conserve biodiversity in the face of human-induced landscape change. We employed microsatellite analysis to examine genetic structure and diversity over small spatial (mostly 1-50 km) and temporal scales (20-50 years) in the squirrel glider (Petaurus norfolcensis), a gliding mammal that is commonly subjected to a loss of habitat connectivity. We identified genetically differentiated local populations over distances as little as 3 km and within 30 years of landscape change. Genetically isolated local populations experienced the loss of genetic diversity, and significantly increased mean relatedness, which suggests increased inbreeding. Where tree cover remained, genetic differentiation was less evident. This pattern was repeated in two landscapes located 750 km apart. These results lend support to other recent studies that suggest the loss of habitat connectivity can produce fine-scale population genetic change in a range of taxa. This gives rise to the prediction that many other vertebrates will experience similar genetic changes. Our results suggest the future collapse of local populations of this gliding mammal is likely unless habitat connectivity is maintained or restored. Landscape management must occur on a fine-scale to avert the erosion of biodiversity. PMID:24386079