Verification Test of the SURF and SURFplus Models in xRage: Part II

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

Menikoff, Ralph

2016-06-20

The previous study used an underdriven detonation wave (steady ZND reaction zone profile followed by a scale invariant rarefaction wave) for PBX 9502 as a validation test of the implementation of the SURF and SURFplus models in the xRage code. Even with a fairly fine uniform mesh (12,800 cells for 100mm) the detonation wave profile had limited resolution due to the thin reaction zone width (0.18mm) for the fast SURF burn rate. Here we study the effect of finer resolution by comparing results of simulations with cell sizes of 8, 2 and 1 μm, which corresponds to 25, 100 andmore » 200 points within the reaction zone. With finer resolution the lead shock pressure is closer to the von Neumann spike pressure, and there is less noise in the rarefaction wave due to fluctuations within the reaction zone. As a result the average error decreases. The pointwise error is still dominated by the smearing the pressure kink in the vicinity of the sonic point which occurs at the end of the reaction zone.« less

Influence of air quality model resolution on uncertainty associated with health impacts

NASA Astrophysics Data System (ADS)

Thompson, T. M.; Selin, N. E.

2012-06-01

We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx), we ran a modeling episode with meteorological inputs representing conditions as they occurred during August through September 2006, and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals) to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between 2, 4 and 12 km resolution runs, but 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements of the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer) resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2 and 4 km resolution. On average, when modeling at 36 km resolution, 7 deaths per ozone month were avoided because of ozone reductions resulting from the proposed emissions reductions (95% confidence interval was 2-9). When modeling at 2, 4 or 12 km finer scale resolution, on average 5 deaths were avoided due to the same reductions (95% confidence interval was 2-7). Initial results for this specific region show that modeling at a resolution finer than 12 km is unlikely to improve uncertainty in benefits analysis. We suggest that 12 km resolution may be appropriate for uncertainty analyses in areas with similar chemistry, but that resolution requirements should be assessed on a case-by-case basis and revised as confidence intervals for concentration-response functions are updated.

A synchrotron-based local computed tomography combined with data-constrained modelling approach for quantitative analysis of anthracite coal microstructure

PubMed Central

Chen, Wen Hao; Yang, Sam Y. S.; Xiao, Ti Qiao; Mayo, Sherry C.; Wang, Yu Dan; Wang, Hai Peng

2014-01-01

Quantifying three-dimensional spatial distributions of pores and material compositions in samples is a key materials characterization challenge, particularly in samples where compositions are distributed across a range of length scales, and where such compositions have similar X-ray absorption properties, such as in coal. Consequently, obtaining detailed information within sub-regions of a multi-length-scale sample by conventional approaches may not provide the resolution and level of detail one might desire. Herein, an approach for quantitative high-definition determination of material compositions from X-ray local computed tomography combined with a data-constrained modelling method is proposed. The approach is capable of dramatically improving the spatial resolution and enabling finer details within a region of interest of a sample larger than the field of view to be revealed than by using conventional techniques. A coal sample containing distributions of porosity and several mineral compositions is employed to demonstrate the approach. The optimal experimental parameters are pre-analyzed. The quantitative results demonstrated that the approach can reveal significantly finer details of compositional distributions in the sample region of interest. The elevated spatial resolution is crucial for coal-bed methane reservoir evaluation and understanding the transformation of the minerals during coal processing. The method is generic and can be applied for three-dimensional compositional characterization of other materials. PMID:24763649

Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales

NASA Astrophysics Data System (ADS)

Caras, Tamir; Hedley, John; Karnieli, Arnon

2017-12-01

Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size < 0.1 m) may compensate for some low spectral resolution drawbacks. In this regard, it is shown that the post-classification majority filtering substantially improves the accuracy of all pixel sizes up to the point where the kernel size reaches the average unit size (pixel < 0.25 m). However, careful investigation as to the effect of band distribution and choice could improve the sensor suitability for the marine environment task. This in mind, while the focus in this study was on the technologically limited spaceborne design, aerial sensors may presently provide an opportunity to implement the suggested setup.

Experimental and Numerical Investigation of Controlled, Small-Scale Motions in a Turbulent Shear Layer

DTIC Science & Technology

2007-06-01

cross flow are taken at finer resolution, down to 6.5 μm/pixel. For the flow mapping, both the CCD camera and part of the laser -sheet optics are...Control of Supersonic Impinging Jet Flows using Microjets . AIAA Journal. 41(7):1347-1355, 2001. [9] M.J. Stanek, G. Raman, V. Kibens, J.A. Ross, J. Odedra

Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario

NASA Astrophysics Data System (ADS)

Singh, G.; Panda, R. K.; Mohanty, B.

2015-12-01

Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.

On the use of high-resolution topographic data as a proxy for seismic site conditions (VS30)

USGS Publications Warehouse

Allen, T.I.; Wald, D.J.

2009-01-01

An alternative method has recently been proposed for evaluating global seismic site conditions, or the average shear velocity to 30 m depth (VS30), from the Shuttle Radar Topography Mission (SRTM) 30 arcsec digital elevation models (DEMs). The basic premise of the method is that the topographic slope can be used as a reliable proxy for VS30 in the absence of geologically and geotechnically based site-condition maps through correlations between VS30 measurements and topographic gradient. Here we evaluate the use of higher-resolution (3 and 9 arcsec) DEMs to examine whether we are able to resolve VS30 in more detail than can be achieved using the lower-resolution SRTM data. High-quality DEMs at resolutions greater than 30 arcsec are not uniformly available at the global scale. However, in many regions where such data exist, they may be employed to resolve finer-scale variations in topographic gradient, and consequently, VS30. We use the U.S. Geological Survey Earth Resources Observation and Science (EROS) Data Center's National Elevation Dataset (NED) to investigate the use of high-resolution DEMs for estimating VS30 in several regions across the United States, including the San Francisco Bay area in California, Los Angeles, California, and St. Louis, Missouri. We compare these results with an example from Taipei, Taiwan, that uses 9 arcsec SRTM data, which are globally available. The use of higher-resolution NED data recovers finer-scale variations in topographic gradient, which better correlate to geological and geomorphic features, in particular, at the transition between hills and basins, warranting their use over 30 arcsec SRTM data where available. However, statistical analyses indicate little to no improvement over lower-resolution topography when compared to VS30 measurements, suggesting that some topographic smoothing may provide more stable VS30 estimates. Furthermore, we find that elevation variability in canopy-based SRTM measurements at resolutions greater than 30 arcsec are too large to resolve reliable slopes, particularly in low-gradient sedimentary basins.

Precision of the anchor influences the amount of adjustment.

PubMed

Janiszewski, Chris; Uy, Dan

2008-02-01

The anchoring-and-adjustment heuristic has been used to account for a wide variety of numerical judgments. Five studies show that adjustment away from a numerical anchor is smaller if the anchor is precise than if it is rounded. Evidence suggests that precise anchors, compared with rounded anchors, are represented on a subjective scale with a finer resolution. If adjustment consists of a series of iterative mental movements along a subjective scale, then an adjustment from a precise anchor should result in a smaller overall correction than an adjustment from a rounded anchor.

A new method to assess the added value of high-resolution regional climate simulations: application to the EURO-CORDEX dataset

NASA Astrophysics Data System (ADS)

Soares, P. M. M.; Cardoso, R. M.

2017-12-01

Regional climate models (RCM) are used with increasing resolutions pursuing to represent in an improved way regional to local scale atmospheric phenomena. The EURO-CORDEX simulations at 0.11° and simulations exploiting finer grid spacing approaching the convective-permitting regimes are representative examples. The climate runs are computationally very demanding and do not always show improvements. These depend on the region, variable and object of study. The gains or losses associated with the use of higher resolution in relation to the forcing model (global climate model or reanalysis), or to different resolution RCM simulations, is known as added value. Its characterization is a long-standing issue, and many different added-value measures have been proposed. In the current paper, a new method is proposed to assess the added value of finer resolution simulations, in comparison to its forcing data or coarser resolution counterparts. This approach builds on a probability density function (PDF) matching score, giving a normalised measure of the difference between diverse resolution PDFs, mediated by the observational ones. The distribution added value (DAV) is an objective added value measure that can be applied to any variable, region or temporal scale, from hindcast or historical (non-synchronous) simulations. The DAVs metric and an application to the EURO-CORDEX simulations, for daily temperatures and precipitation, are here presented. The EURO-CORDEX simulations at both resolutions (0.44o,0.11o) display a clear added value in relation to ERA-Interim, with values around 30% in summer and 20% in the intermediate seasons, for precipitation. When both RCM resolutions are directly compared the added value is limited. The regions with the larger precipitation DAVs are areas where convection is relevant, e.g. Alps and Iberia. When looking at the extreme precipitation PDF tail, the higher resolution improvement is generally greater than the low resolution for seasons and regions. For temperature, the added value is smaller. AcknowledgmentsThe authors wish to acknowledge SOLAR (PTDC/GEOMET/7078/2014) and FCT UID/GEO/50019/ 2013 (Instituto Dom Luiz) projects.

Developing perturbations for Climate Change Impact Assessments

NASA Astrophysics Data System (ADS)

Hewitson, Bruce

Following the 2001 Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report [TAR; IPCC, 2001], and the paucity of climate change impact assessments from developing nations, there has been a significant growth in activities to redress this shortcoming. However, undertaking impact assessments (in relation to malaria, crop stress, regional water supply, etc.) is contingent on available climate-scale scenarios at time and space scales of relevance to the regional issues of importance. These scales are commonly far finer than even the native resolution of the Global Climate Models (GCMs) (the principal tools for climate change research), let alone the skillful resolution (scales of aggregation at which GCM observational error is acceptable for a given application) of GCMs.Consequently, there is a growing demand for regional-scale scenarios, which in turn are reliant on techniques to downscale from GCMs, such as empirical downscaling or nested Regional Climate Models (RCMs). These methods require significant skill, experiential knowledge, and computational infrastructure in order to derive credible regional-scale scenarios. In contrast, it is often the case that impact assessment researchers in developing nations have inadequate resources with limited access to scientists in the broader international scientific community who have the time and expertise to assist. However, where developing effective downscaled scenarios is problematic, it is possible that much useful information can still be obtained for impact assessments by examining the system sensitivity to largerscale climate perturbations. Consequently, one may argue that the early phase of assessing sensitivity and vulnerability should first be characterized by evaluation of the first-order impacts, rather than immediately addressing the finer, secondary factors that are dependant on scenarios derived through downscaling.

Fast ultra-wideband microwave spectral scanning utilizing photonic wavelength- and time-division multiplexing.

PubMed

Li, Yihan; Kuse, Naoya; Fermann, Martin

2017-08-07

A high-speed ultra-wideband microwave spectral scanning system is proposed and experimentally demonstrated. Utilizing coherent dual electro-optical frequency combs and a recirculating optical frequency shifter, the proposed system realizes wavelength- and time-division multiplexing at the same time, offering flexibility between scan speed and size, weight and power requirements (SWaP). High-speed spectral scanning spanning from ~1 to 8 GHz with ~1.2 MHz spectral resolution is achieved experimentally within 14 µs. The system can be easily scaled to higher bandwidth coverage, faster scanning speed or finer spectral resolution with suitable hardware.

CryoSat Plus For Oceans: an ESA Project for CryoSat-2 Data Exploitation Over Ocean

NASA Astrophysics Data System (ADS)

Benveniste, J.; Cotton, D.; Clarizia, M.; Roca, M.; Gommenginger, C. P.; Naeije, M. C.; Labroue, S.; Picot, N.; Fernandes, J.; Andersen, O. B.; Cancet, M.; Dinardo, S.; Lucas, B. M.

2012-12-01

The ESA CryoSat-2 mission is the first space mission to carry a space-borne radar altimeter that is able to operate in the conventional pulsewidth-limited (LRM) mode and in the novel Synthetic Aperture Radar (SAR) mode. Although the prime objective of the Cryosat-2 mission is dedicated to monitoring land and marine ice, the SAR mode capability of the Cryosat-2 SIRAL altimeter also presents the possibility of demonstrating significant potential benefits of SAR altimetry for ocean applications, based on expected performance enhancements which include improved range precision and finer along track spatial resolution. With this scope in mind, the "CryoSat Plus for Oceans" (CP4O) Project, dedicated to the exploitation of CryoSat-2 Data over ocean, supported by the ESA STSE (Support To Science Element) programme, brings together an expert European consortium comprising: DTU Space, isardSAT, National Oceanography Centre , Noveltis, SatOC, Starlab, TU Delft, the University of Porto and CLS (supported by CNES),. The objectives of CP4O are: - to build a sound scientific basis for new scientific and operational applications of Cryosat-2 data over the open ocean, polar ocean, coastal seas and for sea-floor mapping. - to generate and evaluate new methods and products that will enable the full exploitation of the capabilities of the Cryosat-2 SIRAL altimeter , and extend their application beyond the initial mission objectives. - to ensure that the scientific return of the Cryosat-2 mission is maximised. In particular four themes will be addressed: -Open Ocean Altimetry: Combining GOCE Geoid Model with CryoSat Oceanographic LRM Products for the retrieval of CryoSat MSS/MDT model over open ocean surfaces and for analysis of mesoscale and large scale prominent open ocean features. Under this priority the project will also foster the exploitation of the finer resolution and higher SNR of novel CryoSat SAR Data to detect short spatial scale open ocean features. -High Resolution Polar Ocean Altimetry: Combination of GOCE Geoid Model with CryoSat Oceanographic SAR Products over polar oceans for the retrieval of CryoSat MSS/MDT and currents circulations system improving the polar tides models and studying the coupling between blowing wind and current pattern. -High Resolution Coastal Zone Altimetry: Exploitation of the finer resolution and higher SNR of novel CryoSat SAR Data to get the radar altimetry closer to the shore exploiting the SARIn mode for the discrimination of off-nadir land targets (e.g. steep cliffs) in the radar footprint from nadir sea return. -High Resolution Sea-Floor Altimetry: Exploitation of the finer resolution and higher SNR of novel CryoSat SAR Data to resolve the weak short-wavelength sea surface signals caused by sea-floor topography elements and to map uncharted sea-mounts/trenches. One of the first project activities is the consolidation of preliminary scientific requirements for the four themes under investigation. This paper will present the CP4O project content and objectives and will address the first initial results from the on-going work to define the scientific requirements.

A new global anthropogenic heat estimation based on high-resolution nighttime light data

PubMed Central

Yang, Wangming; Luan, Yibo; Liu, Xiaolei; Yu, Xiaoyong; Miao, Lijuan; Cui, Xuefeng

2017-01-01

Consumption of fossil fuel resources leads to global warming and climate change. Apart from the negative impact of greenhouse gases on the climate, the increasing emission of anthropogenic heat from energy consumption also brings significant impacts on urban ecosystems and the surface energy balance. The objective of this work is to develop a new method of estimating the global anthropogenic heat budget and validate it on the global scale with a high precision and resolution dataset. A statistical algorithm was applied to estimate the annual mean anthropogenic heat (AH-DMSP) from 1992 to 2010 at 1×1 km2 spatial resolution for the entire planet. AH-DMSP was validated for both provincial and city scales, and results indicate that our dataset performs well at both scales. Compared with other global anthropogenic heat datasets, the AH-DMSP has a higher precision and finer spatial distribution. Although there are some limitations, the AH-DMSP could provide reliable, multi-scale anthropogenic heat information, which could be used for further research on regional or global climate change and urban ecosystems. PMID:28829436

The spatial and temporal domains of modern ecology.

PubMed

Estes, Lyndon; Elsen, Paul R; Treuer, Timothy; Ahmed, Labeeb; Caylor, Kelly; Chang, Jason; Choi, Jonathan J; Ellis, Erle C

2018-05-01

To understand ecological phenomena, it is necessary to observe their behaviour across multiple spatial and temporal scales. Since this need was first highlighted in the 1980s, technology has opened previously inaccessible scales to observation. To help to determine whether there have been corresponding changes in the scales observed by modern ecologists, we analysed the resolution, extent, interval and duration of observations (excluding experiments) in 348 studies that have been published between 2004 and 2014. We found that observational scales were generally narrow, because ecologists still primarily use conventional field techniques. In the spatial domain, most observations had resolutions ≤1 m 2 and extents ≤10,000 ha. In the temporal domain, most observations were either unreplicated or infrequently repeated (>1 month interval) and ≤1 year in duration. Compared with studies conducted before 2004, observational durations and resolutions appear largely unchanged, but intervals have become finer and extents larger. We also found a large gulf between the scales at which phenomena are actually observed and the scales those observations ostensibly represent, raising concerns about observational comprehensiveness. Furthermore, most studies did not clearly report scale, suggesting that it remains a minor concern. Ecologists can better understand the scales represented by observations by incorporating autocorrelation measures, while journals can promote attentiveness to scale by implementing scale-reporting standards.

Multi-scale coupled modelling of waves and currents on the Catalan shelf.

NASA Astrophysics Data System (ADS)

Grifoll, M.; Warner, J. C.; Espino, M.; Sánchez-Arcilla, A.

2012-04-01

Catalan shelf circulation is characterized by a background along-shelf flow to the southwest (including some meso-scale features) plus episodic storm driven patterns. To investigate these dynamics, a coupled multi-scale modeling system is applied to the Catalan shelf (North-western Mediterranean Sea). The implementation consists of a set of increasing-resolution nested models, based on the circulation model ROMS and the wave model SWAN as part of the COAWST modeling system, covering from the slope and shelf region (~1 km horizontal resolution) down to a local area around Barcelona city (~40 m). The system is initialized with MyOcean products in the coarsest outer domain, and uses atmospheric forcing from other sources for the increasing resolution inner domains. Results of the finer resolution domains exhibit improved agreement with observations relative to the coarser model results. Several hydrodynamic configurations were simulated to determine dominant forcing mechanisms and hydrodynamic processes that control coastal scale processes. The numerical results reveal that the short term (hours to days) inner-shelf variability is strongly influenced by local wind variability, while sea-level slope, baroclinic effects, radiation stresses and regional circulation constitute second-order processes. Additional analysis identifies the significance of shelf/slope exchange fluxes, river discharge and the effect of the spatial resolution of the atmospheric fluxes.

Small-Scale Spectral and Color Analysis of Ritchey Crater Impact Materials

NASA Astrophysics Data System (ADS)

Bray, Veronica; Chojnacki, Matthew; McEwen, Alfred; Heyd, Rodney

2014-11-01

Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) analysis of Ritchey crater on Mars has allowed identification of the minerals uplifted from depth within its central peak as well as the dominant spectral signature of the crater fill materials which surround it. However, the 18m/px resolution of CRISM prevents full analysis of the nature of small-scale dykes, mega breccia blocks and finer scale crater-fill units. We extend our existing CRISM-based compositional mapping of the Ritchey crater interior to sub-CRISM pixel scales with the use of High Resolution Imaging Science Experiment (HiRISE) Color Ratio Products (CRPs). These CRPs are then compared to CRISM images; correlation between color ratio and CRISM spectral signature for a large bedrock unit is defined and used to suggest similar composition for a smaller unit with the same color ratio. Megabreccia deposits, angular fragments of rock in excess of 1 meter in diameter within a finer grained matrix, are common at Ritchey. The dominant spectral signature from each megabreccia unit varies with location around Ritchey and appears to reflect the matrix composition (based on texture and albedo similarities to surrounding rocks) rather than clast composition. In cases where the breccia block size is large enough for CRISM analysis, many different mineral compositions are noted (low calcium pyroxene (LCP) olivine (OL), alteration products) depending on the location. All block compositions (as inferred from CRPs) are observed down to the limit of HiRISE resolution. We have found a variety of dyke compositions within our mapping area. Correlation between CRP color and CRISM spectra in this area suggest that large 10 m wide) dykes within LCP-bearing bedrock close to the crater center tend to have similar composition to the host rock. Smaller dykes running non-parallel to the larger dykes are inferred to be OL-rich suggesting multiple phases of dyke formation within the Ritchey crater and its bedrock.

Influence of air quality model resolution on uncertainty associated with health impacts

NASA Astrophysics Data System (ADS)

Thompson, T. M.; Selin, N. E.

2012-10-01

We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx), we ran a modeling episode with meteorological inputs simulating conditions as they occurred during August through September 2006 (a period representative of conditions leading to high ozone), and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals) to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between the 2, 4 and 12 km resolution runs, but the 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements motivated by Executive Order 12866 as it applies to the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer) resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2, 4 or 12 km resolution. On average, when modeling at 36 km resolution, an estimated 5 deaths per week during the May through September ozone season are avoided because of ozone reductions resulting from the proposed emissions reductions (95% confidence interval was 2-8). When modeling at 2, 4 or 12 km finer scale resolution, on average 4 deaths are avoided due to the same reductions (95% confidence interval was 1-7). Study results show that ozone modeling at a resolution finer than 12 km is unlikely to reduce uncertainty in benefits analysis for this specific region. We suggest that 12 km resolution may be appropriate for uncertainty analyses of health impacts due to ozone control scenarios, in areas with similar chemistry, meteorology and population density, but that resolution requirements should be assessed on a case-by-case basis and revised as confidence intervals for concentration-response functions are updated.

Evaluation of MODIS Albedo Product (MCD43A) over Grassland, Agriculture and Forest Surface Types During Dormant and Snow-Covered Periods

NASA Technical Reports Server (NTRS)

Wang, Zhousen; Schaaf, Crystal B.; Strahler, Alan H.; Chopping, Mark J.; Roman, Miguel O.; Shuai, Yanmin; Woodcock, Curtis E.; Hollinger, David Y.; Fitzjarrald, David R.

2013-01-01

This study assesses the Moderate-resolution Imaging Spectroradiometer (MODIS) BRDF/albedo 8 day standard product and products from the daily Direct Broadcast BRDF/albedo algorithm, and shows that these products agree well with ground-based albedo measurements during the more difficult periods of vegetation dormancy and snow cover. Cropland, grassland, deciduous and coniferous forests are considered. Using an integrated validation strategy, analyses of the representativeness of the surface heterogeneity under both dormant and snow-covered situations are performed to decide whether direct comparisons between ground measurements and 500-m satellite observations can be made or whether finer spatial resolution airborne or spaceborne data are required to scale the results at each location. Landsat Enhanced Thematic Mapper Plus (ETM +) data are used to generate finer scale representations of albedo at each location to fully link ground data with satellite data. In general, results indicate the root mean square errors (RMSEs) are less than 0.030 over spatially representative sites of agriculture/grassland during the dormant periods and less than 0.050 during the snow-covered periods for MCD43A albedo products. For forest, the RMSEs are less than 0.020 during the dormant period and 0.025 during the snow-covered periods. However, a daily retrieval strategy is necessary to capture ephemeral snow events or rapidly changing situations such as the spring snow melt.

Hierarchical nucleus segmentation in digital pathology images

NASA Astrophysics Data System (ADS)

Gao, Yi; Ratner, Vadim; Zhu, Liangjia; Diprima, Tammy; Kurc, Tahsin; Tannenbaum, Allen; Saltz, Joel

2016-03-01

Extracting nuclei is one of the most actively studied topic in the digital pathology researches. Most of the studies directly search the nuclei (or seeds for the nuclei) from the finest resolution available. While the richest information has been utilized by such approaches, it is sometimes difficult to address the heterogeneity of nuclei in different tissues. In this work, we propose a hierarchical approach which starts from the lower resolution level and adaptively adjusts the parameters while progressing into finer and finer resolution. The algorithm is tested on brain and lung cancers images from The Cancer Genome Atlas data set.

HiPS - Hierarchical Progressive Survey Version 1.0

NASA Astrophysics Data System (ADS)

Fernique, Pierre; Allen, Mark; Boch, Thomas; Donaldson, Tom; Durand, Daniel; Ebisawa, Ken; Michel, Laurent; Salgado, Jesus; Stoehr, Felix; Fernique, Pierre

2017-05-01

This document presents HiPS, a hierarchical scheme for the description, storage and access of sky survey data. The system is based on hierarchical tiling of sky regions at finer and finer spatial resolution which facilitates a progressive view of a survey, and supports multi-resolution zooming and panning. HiPS uses the HEALPix tessellation of the sky as the basis for the scheme and is implemented as a simple file structure with a direct indexing scheme that leads to practical implementations.

Wiener-matrix image restoration beyond the sampling passband

NASA Technical Reports Server (NTRS)

Rahman, Zia-Ur; Alter-Gartenberg, Rachel; Fales, Carl L.; Huck, Friedrich O.

1991-01-01

A finer-than-sampling-lattice resolution image can be obtained using multiresponse image gathering and Wiener-matrix restoration. The multiresponse image gathering weighs the within-passband and aliased signal components differently, allowing the Wiener-matrix restoration filter to unscramble these signal components and restore spatial frequencies beyond the sampling passband of the photodetector array. A multiresponse images can be reassembled into a single minimum mean square error image with a resolution that is sq rt A times finer than the photodetector-array sampling lattice.

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

NASA Astrophysics Data System (ADS)

Fenech, Sara; Doherty, Ruth M.; Heaviside, Clare; Vardoulakis, Sotiris; Macintyre, Helen L.; O'Connor, Fiona M.

2018-04-01

We examine the impact of model horizontal resolution on simulated concentrations of surface ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5), and the associated health impacts over Europe, using the HadGEM3-UKCA chemistry-climate model to simulate pollutant concentrations at a coarse (˜ 140 km) and a finer (˜ 50 km) resolution. The attributable fraction (AF) of total mortality due to long-term exposure to warm season daily maximum 8 h running mean (MDA8) O3 and annual-average PM2.5 concentrations is then calculated for each European country using pollutant concentrations simulated at each resolution. Our results highlight a seasonal variation in simulated O3 and PM2.5 differences between the two model resolutions in Europe. Compared to the finer resolution results, simulated European O3 concentrations at the coarse resolution are higher on average in winter and spring (˜ 10 and ˜ 6 %, respectively). In contrast, simulated O3 concentrations at the coarse resolution are lower in summer and autumn (˜ -1 and ˜ -4 %, respectively). These differences may be partly explained by differences in nitrogen dioxide (NO2) concentrations simulated at the two resolutions. Compared to O3, we find the opposite seasonality in simulated PM2.5 differences between the two resolutions. In winter and spring, simulated PM2.5 concentrations are lower at the coarse compared to the finer resolution (˜ -8 and ˜ -6 %, respectively) but higher in summer and autumn (˜ 29 and ˜ 8 %, respectively). Simulated PM2.5 values are also mostly related to differences in convective rainfall between the two resolutions for all seasons. These differences between the two resolutions exhibit clear spatial patterns for both pollutants that vary by season, and exert a strong influence on country to country variations in estimated AF for the two resolutions. Warm season MDA8 O3 levels are higher in most of southern Europe, but lower in areas of northern and eastern Europe when simulated at the coarse resolution compared to the finer resolution. Annual-average PM2.5 concentrations are higher across most of northern and eastern Europe but lower over parts of southwest Europe at the coarse compared to the finer resolution. Across Europe, differences in the AF associated with long-term exposure to population-weighted MDA8 O3 range between -0.9 and +2.6 % (largest positive differences in southern Europe), while differences in the AF associated with long-term exposure to population-weighted annual mean PM2.5 range from -4.7 to +2.8 % (largest positive differences in eastern Europe) of the total mortality. Therefore this study, with its unique focus on Europe, demonstrates that health impact assessments calculated using modelled pollutant concentrations, are sensitive to a change in model resolution by up to ˜ ±5 % of the total mortality across Europe.

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.

Single-Image Super-Resolution Based on Rational Fractal Interpolation.

PubMed

Zhang, Yunfeng; Fan, Qinglan; Bao, Fangxun; Liu, Yifang; Zhang, Caiming

2018-08-01

This paper presents a novel single-image super-resolution (SR) procedure, which upscales a given low-resolution (LR) input image to a high-resolution image while preserving the textural and structural information. First, we construct a new type of bivariate rational fractal interpolation model and investigate its analytical properties. This model has different forms of expression with various values of the scaling factors and shape parameters; thus, it can be employed to better describe image features than current interpolation schemes. Furthermore, this model combines the advantages of rational interpolation and fractal interpolation, and its effectiveness is validated through theoretical analysis. Second, we develop a single-image SR algorithm based on the proposed model. The LR input image is divided into texture and non-texture regions, and then, the image is interpolated according to the characteristics of the local structure. Specifically, in the texture region, the scaling factor calculation is the critical step. We present a method to accurately calculate scaling factors based on local fractal analysis. Extensive experiments and comparisons with the other state-of-the-art methods show that our algorithm achieves competitive performance, with finer details and sharper edges.

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.

Optical instruments synergy in determination of optical depth of thin clouds

NASA Astrophysics Data System (ADS)

Viviana Vlăduţescu, Daniela; Schwartz, Stephen E.; Huang, Dong

2018-04-01

Optically thin clouds have a strong radiative effect and need to be represented accurately in climate models. Cloud optical depth of thin clouds was retrieved using high resolution digital photography, lidar, and a radiative transfer model. The Doppler Lidar was operated at 1.5 μm, minimizing return from Rayleigh scattering, emphasizing return from aerosols and clouds. This approach examined cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opening new avenues for examination of cloud structure and evolution.

Optical Instruments Synergy in Determination of Optical Depth of Thin Clouds

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

Vladutescu, Daniela V.; Schwartz, Stephen E.

Optically thin clouds have a strong radiative effect and need to be represented accurately in climate models. Cloud optical depth of thin clouds was retrieved using high resolution digital photography, lidar, and a radiative transfer model. The Doppler Lidar was operated at 1.5 μm, minimizing return from Rayleigh scattering, emphasizing return from aerosols and clouds. This approach examined cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opening new avenues for examination of cloud structure and evolution.

Resolving the fine-scale structure in turbulent Rayleigh-Bénard convection

NASA Astrophysics Data System (ADS)

Scheel, Janet D.; Emran, Mohammad S.; Schumacher, Jörg

2013-11-01

We present high-resolution direct numerical simulation studies of turbulent Rayleigh-Bénard convection in a closed cylindrical cell with an aspect ratio of one. The focus of our analysis is on the finest scales of convective turbulence, in particular the statistics of the kinetic energy and thermal dissipation rates in the bulk and the whole cell. The fluctuations of the energy dissipation field can directly be translated into a fluctuating local dissipation scale which is found to develop ever finer fluctuations with increasing Rayleigh number. The range of these scales as well as the probability of high-amplitude dissipation events decreases with increasing Prandtl number. In addition, we examine the joint statistics of the two dissipation fields and the consequences of high-amplitude events. We have also investigated the convergence properties of our spectral element method and have found that both dissipation fields are very sensitive to insufficient resolution. We demonstrate that global transport properties, such as the Nusselt number, and the energy balances are partly insensitive to insufficient resolution and yield correct results even when the dissipation fields are under-resolved. Our present numerical framework is also compared with high-resolution simulations which use a finite difference method. For most of the compared quantities the agreement is found to be satisfactory.

Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

NASA Astrophysics Data System (ADS)

McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross

2017-12-01

Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.

The Australian National Airborne Field Experiment 2005: Soil Moisture Remote Sensing at 60 Meter Resolution and Up

NASA Technical Reports Server (NTRS)

Kim, E. J.; Walker, J. P.; Panciera, R.; Kalma, J. D.

2006-01-01

Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground truth collection over a range of grid spacings, to provide a basis for examining the effects of subpixel variability. However, the native footprint size of the airborne L-band radiometers was always a few hundred meters. During the recently completed (November, 2005) National Airborne Field Experiment (NAFE) campaign in Australia, a compact L-band radiometer was deployed on a small aircraft. This new combination permitted routine observations at native resolutions as high as 60 meters, substantially finer than in previous airborne soil moisture campaigns, as well as satellite footprint areal coverage. The radiometer, the Polarimetric L-band Microwave Radiometer (PLMR) performed extremely well and operations included extensive calibration-related observations. Thus, along with the extensive fine-scale ground truth, the NAFE dataset includes all the ingredients for the first scaling studies involving very-high-native resolution soil moisture observations and the effects of vegetation, roughness, etc. A brief overview of the NAFE will be presented, then examples of the airborne observations with resolutions from 60 m to 1 km will be shown, and early results from scaling studies will be discussed.

Using multi-scale sampling and spatial cross-correlation to investigate patterns of plant species richness

USGS Publications Warehouse

Kalkhan, M.A.; Stohlgren, T.J.

2000-01-01

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, IYZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m2) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m2 subplots within each of the 1000 m2 plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.

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

Wang, Jiali; Swati, F. N. U.; Stein, Michael L.

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, andmore » time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.« less

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

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.

Interannual rainfall variability over China in the MetUM GA6 and GC2 configurations

NASA Astrophysics Data System (ADS)

Stephan, Claudia Christine; Klingaman, Nicholas P.; Vidale, Pier Luigi; Turner, Andrew G.; Demory, Marie-Estelle; Guo, Liang

2018-05-01

Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyse the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ˜ 200, 90 and 40 km in the zonal direction at the equator, respectively) are analysed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China but improve with finer resolution and coupling. Empirical orthogonal teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal mean time series. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

The Role of Moist Processes in the Intrinsic Predictability of Indian Ocean Cyclones

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

Taraphdar, Sourav; Mukhopadhyay, P.; Leung, Lai-Yung R.

The role of moist processes and the possibility of error cascade from cloud scale processes affecting the intrinsic predictable time scale of a high resolution convection permitting model within the environment of tropical cyclones (TCs) over the Indian region are investigated. Consistent with past studies of extra-tropical cyclones, it is demonstrated that moist processes play a major role in forecast error growth which may ultimately limit the intrinsic predictability of the TCs. Small errors in the initial conditions may grow rapidly and cascades from smaller scales to the larger scales through strong diabatic heating and nonlinearities associated with moist convection.more » Results from a suite of twin perturbation experiments for four tropical cyclones suggest that the error growth is significantly higher in cloud permitting simulation at 3.3 km resolutions compared to simulations at 3.3 km and 10 km resolution with parameterized convection. Convective parameterizations with prescribed convective time scales typically longer than the model time step allows the effects of microphysical tendencies to average out so convection responds to a smoother dynamical forcing. Without convective parameterizations, the finer-scale instabilities resolved at 3.3 km resolution and stronger vertical motion that results from the cloud microphysical parameterizations removing super-saturation at each model time step can ultimately feed the error growth in convection permitting simulations. This implies that careful considerations and/or improvements in cloud parameterizations are needed if numerical predictions are to be improved through increased model resolution. Rapid upscale error growth from convective scales may ultimately limit the intrinsic mesoscale predictability of the TCs, which further supports the needs for probabilistic forecasts of these events, even at the mesoscales.« less

Nested high-resolution large-eddy simulations in WRF to support wind power

NASA Astrophysics Data System (ADS)

Mirocha, J.; Kirkil, G.; Kosovic, B.; Lundquist, J. K.

2009-12-01

The WRF model’s grid nesting capability provides a potentially powerful framework for simulating flow over a wide range of scales. One such application is computation of realistic inflow boundary conditions for large eddy simulations (LES) by nesting LES domains within mesoscale domains. While nesting has been widely and successfully applied at GCM to mesoscale resolutions, the WRF model’s nesting behavior at the high-resolution (Δx < 1000m) end of the spectrum is less well understood. Nesting LES within msoscale domains can significantly improve turbulent flow prediction at the scale of a wind park, providing a basis for superior site characterization, or for improved simulation of turbulent inflows encountered by turbines. We investigate WRF’s grid nesting capability at high mesh resolutions using nested mesoscale and large-eddy simulations. We examine the spatial scales required for flow structures to equilibrate to the finer mesh as flow enters a nest, and how the process depends on several parameters, including grid resolution, turbulence subfilter stress models, relaxation zones at nest interfaces, flow velocities, surface roughnesses, terrain complexity and atmospheric stability. Guidance on appropriate domain sizes and turbulence models for LES in light of these results is provided This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 LLNL-ABS-416482

Scaling of surface energy fluxes using remotely sensed data

NASA Astrophysics Data System (ADS)

French, Andrew Nichols

Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates derived from data taken at about 400-m resolution (the operational scale at El Reno) were susceptible to large error due to mixing of surface types. The El Reno experiments show that accurate instantaneous estimates of ET require precise image alignment and image resolutions finer than landscape operational scale. These findings are valuable for the design of sensors and experiments to quantify spatially-varying hydrologic processes.

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

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

Multi Scale Modeling of Continuous Aramid Fiber Reinforced Polymer Matrix Composites Used in Ballistic Protection Applications

DTIC Science & Technology

2014-11-16

related to identification of the type and the extent of data generated at a finer length scale to the adjacent coarser length scale, as well as seamless ...data generated at a finer length scale to the adjacent coarser length scale, as well as seamless integration of different length scales into a unified...composite laminate consisting of 32 laminae and impacted (at a 0° obliquity angle and an incident velocity of 500 m/s) by a 0.30 caliber steel

Fine-Scale Population Estimation by 3D Reconstruction of Urban Residential Buildings

PubMed Central

Wang, Shixin; Tian, Ye; Zhou, Yi; Liu, Wenliang; Lin, Chenxi

2016-01-01

Fine-scale population estimation is essential in emergency response and epidemiological applications as well as urban planning and management. However, representing populations in heterogeneous urban regions with a finer resolution is a challenge. This study aims to obtain fine-scale population distribution based on 3D reconstruction of urban residential buildings with morphological operations using optical high-resolution (HR) images from the Chinese No. 3 Resources Satellite (ZY-3). Specifically, the research area was first divided into three categories when dasymetric mapping was taken into consideration. The results demonstrate that the morphological building index (MBI) yielded better results than built-up presence index (PanTex) in building detection, and the morphological shadow index (MSI) outperformed color invariant indices (CIIT) in shadow extraction and height retrieval. Building extraction and height retrieval were then combined to reconstruct 3D models and to estimate population. Final results show that this approach is effective in fine-scale population estimation, with a mean relative error of 16.46% and an overall Relative Total Absolute Error (RATE) of 0.158. This study gives significant insights into fine-scale population estimation in complicated urban landscapes, when detailed 3D information of buildings is unavailable. PMID:27775670

Pore-scale dynamics of salt transport and distribution in drying porous media

NASA Astrophysics Data System (ADS)

Shokri, Nima

2014-01-01

Understanding the physics of water evaporation from saline porous media is important in many natural and engineering applications such as durability of building materials and preservation of monuments, water quality, and mineral-fluid interactions. We applied synchrotron x-ray micro-tomography to investigate the pore-scale dynamics of dissolved salt distribution in a three dimensional drying saline porous media using a cylindrical plastic column (15 mm in height and 8 mm in diameter) packed with sand particles saturated with CaI2 solution (5% concentration by mass) with a spatial and temporal resolution of 12 μm and 30 min, respectively. Every time the drying sand column was set to be imaged, two different images were recorded using distinct synchrotron x-rays energies immediately above and below the K-edge value of Iodine. Taking the difference between pixel gray values enabled us to delineate the spatial and temporal distribution of CaI2 concentration at pore scale. Results indicate that during early stages of evaporation, air preferentially invades large pores at the surface while finer pores remain saturated and connected to the wet zone at bottom via capillary-induced liquid flow acting as evaporating spots. Consequently, the salt concentration increases preferentially in finer pores where evaporation occurs. Higher salt concentration was observed close to the evaporating surface indicating a convection-driven process. The obtained salt profiles were used to evaluate the numerical solution of the convection-diffusion equation (CDE). Results show that the macro-scale CDE could capture the overall trend of the measured salt profiles but fail to produce the exact slope of the profiles. Our results shed new insight on the physics of salt transport and its complex dynamics in drying porous media and establish synchrotron x-ray tomography as an effective tool to investigate the dynamics of salt transport in porous media at high spatial and temporal resolution.

Pore-scale dynamics of salt transport and distribution in drying porous media

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

Shokri, Nima, E-mail: nima.shokri@manchester.ac.uk

2014-01-15

Understanding the physics of water evaporation from saline porous media is important in many natural and engineering applications such as durability of building materials and preservation of monuments, water quality, and mineral-fluid interactions. We applied synchrotron x-ray micro-tomography to investigate the pore-scale dynamics of dissolved salt distribution in a three dimensional drying saline porous media using a cylindrical plastic column (15 mm in height and 8 mm in diameter) packed with sand particles saturated with CaI{sub 2} solution (5% concentration by mass) with a spatial and temporal resolution of 12 μm and 30 min, respectively. Every time the drying sandmore » column was set to be imaged, two different images were recorded using distinct synchrotron x-rays energies immediately above and below the K-edge value of Iodine. Taking the difference between pixel gray values enabled us to delineate the spatial and temporal distribution of CaI{sub 2} concentration at pore scale. Results indicate that during early stages of evaporation, air preferentially invades large pores at the surface while finer pores remain saturated and connected to the wet zone at bottom via capillary-induced liquid flow acting as evaporating spots. Consequently, the salt concentration increases preferentially in finer pores where evaporation occurs. Higher salt concentration was observed close to the evaporating surface indicating a convection-driven process. The obtained salt profiles were used to evaluate the numerical solution of the convection-diffusion equation (CDE). Results show that the macro-scale CDE could capture the overall trend of the measured salt profiles but fail to produce the exact slope of the profiles. Our results shed new insight on the physics of salt transport and its complex dynamics in drying porous media and establish synchrotron x-ray tomography as an effective tool to investigate the dynamics of salt transport in porous media at high spatial and temporal resolution.« less

Scales of snow depth variability in high elevation rangeland sagebrush

NASA Astrophysics Data System (ADS)

Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

2017-09-01

In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

Sentinel-3A Views Ocean Variability More Accurately at Finer Resolution

NASA Astrophysics Data System (ADS)

Heslop, E. E.; Sánchez-Román, A.; Pascual, A.; Rodríguez, D.; Reeve, K. A.; Faugère, Y.; Raynal, M.

2017-12-01

This is the first multiplatform evaluation involving data from the new Sentinel-3A altimeter. An experiment was undertaken in the Algerian Basin, employing an ocean glider and a ship mission, along the same track and synchronous with an overpass of the Sentinel-3A mission. This provided three independent views of the ocean velocity field, along a section that encompassed three different oceanographic regimes. The results demonstrate the capacity of Sentinel-3A to retrieve fine-scale oceanographic features ( 20 km). The intercomparison with in situ platforms showed a significant improvement, order 30% in resolution and 42% in velocity accuracy using a synthetic aperture radar mode with respect to lower-resolution mode of conventional altimetry. In addition, the three-platform view provided valuable insight into the variability of evolving oceanographic features, in an area of the Mediterranean that remains chronically under sampled.

Simulation of Anomalous Regional Climate Events with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

1999-01-01

The stretched-grid approach provides an efficient down-scaling and consistent interactions between global and regional scales due to using one variable-resolution model for integrations. It is a workable alternative to the widely used nested-grid approach introduced over a decade ago as a pioneering step in regional climate modeling. A variable-resolution General Circulation Model (GCM) employing a stretched grid, with enhanced resolution over the US as the area of interest, is used for simulating two anomalous regional climate events, the US summer drought of 1988 and flood of 1993. The special mode of integration using a stretched-grid GCM and data assimilation system is developed that allows for imitating the nested-grid framework. The mode is useful for inter-comparison purposes and for underlining the differences between these two approaches. The 1988 and 1993 integrations are performed for the two month period starting from mid May. Regional resolutions used in most of the experiments is 60 km. The major goal and the result of the study is obtaining the efficient down-scaling over the area of interest. The monthly mean prognostic regional fields for the stretched-grid integrations are remarkably close to those of the verifying analyses. Simulated precipitation patterns are successfully verified against gauge precipitation observations. The impact of finer 40 km regional resolution is investigated for the 1993 integration and an example of recovering subregional precipitation is presented. The obtained results show that the global variable-resolution stretched-grid approach is a viable candidate for regional and subregional climate studies and applications.

Prospects for improving the representation of coastal and shelf seas in global ocean models

NASA Astrophysics Data System (ADS)

Holt, Jason; Hyder, Patrick; Ashworth, Mike; Harle, James; Hewitt, Helene T.; Liu, Hedong; New, Adrian L.; Pickles, Stephen; Porter, Andrew; Popova, Ekaterina; Icarus Allen, J.; Siddorn, John; Wood, Richard

2017-02-01

Accurately representing coastal and shelf seas in global ocean models represents one of the grand challenges of Earth system science. They are regions of immense societal importance through the goods and services they provide, hazards they pose and their role in global-scale processes and cycles, e.g. carbon fluxes and dense water formation. However, they are poorly represented in the current generation of global ocean models. In this contribution, we aim to briefly characterise the problem, and then to identify the important physical processes, and their scales, needed to address this issue in the context of the options available to resolve these scales globally and the evolving computational landscape.We find barotropic and topographic scales are well resolved by the current state-of-the-art model resolutions, e.g. nominal 1/12°, and still reasonably well resolved at 1/4°; here, the focus is on process representation. We identify tides, vertical coordinates, river inflows and mixing schemes as four areas where modelling approaches can readily be transferred from regional to global modelling with substantial benefit. In terms of finer-scale processes, we find that a 1/12° global model resolves the first baroclinic Rossby radius for only ˜ 8 % of regions < 500 m deep, but this increases to ˜ 70 % for a 1/72° model, so resolving scales globally requires substantially finer resolution than the current state of the art.We quantify the benefit of improved resolution and process representation using 1/12° global- and basin-scale northern North Atlantic nucleus for a European model of the ocean (NEMO) simulations; the latter includes tides and a k-ɛ vertical mixing scheme. These are compared with global stratification observations and 19 models from CMIP5. In terms of correlation and basin-wide rms error, the high-resolution models outperform all these CMIP5 models. The model with tides shows improved seasonal cycles compared to the high-resolution model without tides. The benefits of resolution are particularly apparent in eastern boundary upwelling zones.To explore the balance between the size of a globally refined model and that of multiscale modelling options (e.g. finite element, finite volume or a two-way nesting approach), we consider a simple scale analysis and a conceptual grid refining approach. We put this analysis in the context of evolving computer systems, discussing model turnaround time, scalability and resource costs. Using a simple cost model compared to a reference configuration (taken to be a 1/4° global model in 2011) and the increasing performance of the UK Research Councils' computer facility, we estimate an unstructured mesh multiscale approach, resolving process scales down to 1.5 km, would use a comparable share of the computer resource by 2021, the two-way nested multiscale approach by 2022, and a 1/72° global model by 2026. However, we also note that a 1/12° global model would not have a comparable computational cost to a 1° global model in 2017 until 2027. Hence, we conclude that for computationally expensive models (e.g. for oceanographic research or operational oceanography), resolving scales to ˜ 1.5 km would be routinely practical in about a decade given substantial effort on numerical and computational development. For complex Earth system models, this extends to about 2 decades, suggesting the focus here needs to be on improved process parameterisation to meet these challenges.

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

End of the chain? Rugosity and fine-scale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology

USGS Publications Warehouse

Storlazzi, Curt; Dartnell, Peter; Hatcher, Gerry; Gibbs, Ann E.

2016-01-01

The rugosity or complexity of the seafloor has been shown to be an important ecological parameter for fish, algae, and corals. Historically, rugosity has been measured either using simple and subjective manual methods such as ‘chain-and-tape’ or complicated and expensive geophysical methods. Here, we demonstrate the application of structure-from-motion (SfM) photogrammetry to generate high-resolution, three-dimensional bathymetric models of a fringing reef from existing underwater video collected to characterize the seafloor. SfM techniques are capable of achieving spatial resolution that can be orders of magnitude greater than large-scale lidar and sonar mapping of coral reef ecosystems. The resulting data provide finer-scale measurements of bathymetry and rugosity that are more applicable to ecological studies of coral reefs than provided by the more expensive and time-consuming geophysical methods. Utilizing SfM techniques for characterizing the benthic habitat proved to be more effective and quantitatively powerful than conventional methods and thus might portend the end of the ‘chain-and-tape’ method for measuring benthic complexity.

Identifying the scale-dependent motifs in atmospheric surface layer by ordinal pattern analysis

NASA Astrophysics Data System (ADS)

Li, Qinglei; Fu, Zuntao

2018-07-01

Ramp-like structures in various atmospheric surface layer time series have been long studied, but the presence of motifs with the finer scale embedded within larger scale ramp-like structures has largely been overlooked in the reported literature. Here a novel, objective and well-adapted methodology, the ordinal pattern analysis, is adopted to study the finer-scaled motifs in atmospheric boundary-layer (ABL) time series. The studies show that the motifs represented by different ordinal patterns take clustering properties and 6 dominated motifs out of the whole 24 motifs account for about 45% of the time series under particular scales, which indicates the higher contribution of motifs with the finer scale to the series. Further studies indicate that motif statistics are similar for both stable conditions and unstable conditions at larger scales, but large discrepancies are found at smaller scales, and the frequencies of motifs "1234" and/or "4321" are a bit higher under stable conditions than unstable conditions. Under stable conditions, there are great changes for the occurrence frequencies of motifs "1234" and "4321", where the occurrence frequencies of motif "1234" decrease from nearly 24% to 4.5% with the scale factor increasing, and the occurrence frequencies of motif "4321" change nonlinearly with the scale increasing. These great differences of dominated motifs change with scale can be taken as an indicator to quantify the flow structure changes under different stability conditions, and motif entropy can be defined just by only 6 dominated motifs to quantify this time-scale independent property of the motifs. All these results suggest that the defined scale of motifs with the finer scale should be carefully taken into consideration in the interpretation of turbulence coherent structures.

Dark energy with fine redshift sampling

NASA Astrophysics Data System (ADS)

Linder, Eric V.

2007-03-01

The cosmological constant and many other possible origins for acceleration of the cosmic expansion possess variations in the dark energy properties slow on the Hubble time scale. Given that models with more rapid variation, or even phase transitions, are possible though, we examine the fineness in redshift with which cosmological probes can realistically be employed, and what constraints this could impose on dark energy behavior. In particular, we discuss various aspects of baryon acoustic oscillations, and their use to measure the Hubble parameter H(z). We find that currently considered cosmological probes have an innate resolution no finer than Δz≈0.2 0.3.

Diagnosing isopycnal diffusivity in an eddying, idealized midlatitude ocean basin via Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT)

DOE PAGES

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

How Much Can Remotely-Sensed Natural Resource Inventories Benefit from Finer Spatial Resolutions?

NASA Astrophysics Data System (ADS)

Hou, Z.; Xu, Q.; McRoberts, R. E.; Ståhl, G.; Greenberg, J. A.

2017-12-01

For remote sensing facilitated natural resource inventories, the effects of spatial resolution in the form of pixel size and the effects of subpixel information on estimates of population parameters were evaluated by comparing results obtained using Landsat 8 and RapidEye auxiliary imagery. The study area was in Burkina Faso, and the variable of interest was the stem volume (m3/ha) convertible to the woodland aboveground biomass. A sample consisting of 160 field plots was selected and measured from the population following a two-stage sampling design. Models were fit using weighted least squares; the population mean, mu, and the variance of the estimator of the population mean, Var(mu.hat), were estimated in two inferential frameworks, model-based and model-assisted, and compared; for each framework, Var(mu.hat) was estimated both analytically and empirically. Empirical variances were estimated with bootstrapping that for resampling takes clustering effects into account. The primary results were twofold. First, for the effects of spatial resolution and subpixel information, four conclusions are relevant: (1) finer spatial resolution imagery indeed contributes to greater precision for estimators of population parameter, but this increase is slight at a maximum rate of 20% considering that RapidEye data are 36 times finer resolution than Landsat 8 data; (2) subpixel information on texture is marginally beneficial when it comes to making inference for population of large areas; (3) cost-effectiveness is more favorable for the free of charge Landsat 8 imagery than RapidEye imagery; and (4) for a given plot size, candidate remote sensing auxiliary datasets are more cost-effective when their spatial resolutions are similar to the plot size than with much finer alternatives. Second, for the comparison between estimators, three conclusions are relevant: (1) model-based variance estimates are consistent with each other and about half as large as stabilized model-assisted estimates, suggesting superior effectiveness of model-based inference to model-assisted inference; (2) bootstrapping is an effective alternative to analytical variance estimators; and (3) prediction accuracy expressed by RMSE is useful for screening candidate models to be used for population inferences.

Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records.

PubMed

Foreman, Brady Z; Straub, Kyle M

2017-09-01

Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 10 4 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation.

Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records

PubMed Central

Foreman, Brady Z.; Straub, Kyle M.

2017-01-01

Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 104 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation. PMID:28924607

LLNL Scientists Use NERSC to Advance Global Aerosol Simulations

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

Bergmann, D J; Chuang, C; Rotman, D

2004-10-13

While ''greenhouse gases'' have been the focus of climate change research for a number of years, DOE's ''Aerosol Initiative'' is now examining how aerosols (small particles of approximately micron size) affect the climate on both a global and regional scale. Scientists in the Atmospheric Science Division at Lawrence Livermore National Laboratory (LLNL) are using NERSC's IBM supercomputer and LLNL's IMPACT (atmospheric chemistry) model to perform simulations showing the historic effects of sulfur aerosols at a finer spatial resolution than ever done before. Simulations were carried out for five decades, from the 1950s through the 1990s. The results clearly show themore » effects of the changing global pattern of sulfur emissions. Whereas in 1950 the United States emitted 41 percent of the world's sulfur aerosols, this figure had dropped to 15 percent by 1990, due to conservation and anti-pollution policies. By contrast, the fraction of total sulfur emissions of European origin has only dropped by a factor of 2 and the Asian emission fraction jumped six fold during the same time, from 7 percent in 1950 to 44 percent in 1990. Under a special allocation of computing time provided by the Office of Science INCITE (Innovative and Novel Computational Impact on Theory and Experiment) program, Dan Bergmann, working with a team of LLNL scientists including Cathy Chuang, Philip Cameron-Smith, and Bala Govindasamy, was able to carry out a large number of calculations during the past month, making the aerosol project one of the largest users of NERSC resources. The applications ran on 128 and 256 processors. The objective was to assess the effects of anthropogenic (man-made) sulfate aerosols. The IMPACT model calculates the rate at which SO{sub 2} (a gas emitted by industrial activity) is oxidized and forms particles known as sulfate aerosols. These particles have a short lifespan in the atmosphere, often washing out in about a week. This means that their effects on climate tend to be more regional, occurring near the area where the SO{sub 2} is emitted. To accurately study these regional effects, Bergmann needed to run the simulations at a finer horizontal resolution, as the coarser resolution (typically 300km by 300km) of other climate models are insufficient for studying changes on a regional scale. Livermore's use of CAM3, the Community Atmospheric Model which is a high-resolution climate model developed at NCAR (with collaboration from DOE), allows a 100km by 100km grid to be applied. NERSC's terascale computing capability provided the needed computational horsepower to run the application at the finer level.« less

The impact of climate change measured at relevant spatial scales: new hope for tropical lizards.

PubMed

Logan, Michael L; Huynh, Ryan K; Precious, Rachel A; Calsbeek, Ryan G

2013-10-01

Much attention has been given to recent predictions that widespread extinctions of tropical ectotherms, and tropical forest lizards in particular, will result from anthropogenic climate change. Most of these predictions, however, are based on environmental temperature data measured at a maximum resolution of 1 km(2), whereas individuals of most species experience thermal variation on a much finer scale. To address this disconnect, we combined thermal performance curves for five populations of Anolis lizard from the Bay Islands of Honduras with high-resolution temperature distributions generated from physical models. Previous research has suggested that open-habitat species are likely to invade forest habitat and drive forest species to extinction. We test this hypothesis, and compare the vulnerabilities of closely related, but allopatric, forest species. Our data suggest that the open-habitat populations we studied will not invade forest habitat and may actually benefit from predicted warming for many decades. Conversely, one of the forest species we studied should experience reduced activity time as a result of warming, while two others are unlikely to experience a significant decline in performance. Our results suggest that global-scale predictions generated using low-resolution temperature data may overestimate the vulnerability of many tropical ectotherms to climate change. © 2013 John Wiley & Sons Ltd.

The influence of model resolution on ozone in industrial volatile organic compound plumes.

PubMed

Henderson, Barron H; Jeffries, Harvey E; Kim, Byeong-Uk; Vizuete, William G

2010-09-01

Regions with concentrated petrochemical industrial activity (e.g., Houston or Baton Rouge) frequently experience large, localized releases of volatile organic compounds (VOCs). Aircraft measurements suggest these released VOCs create plumes with ozone (O3) production rates 2-5 times higher than typical urban conditions. Modeling studies found that simulating high O3 productions requires superfine (1-km) horizontal grid cell size. Compared with fine modeling (4-kmin), the superfine resolution increases the peak O3 concentration by as much as 46%. To understand this drastic O3 change, this study quantifies model processes for O3 and "odd oxygen" (Ox) in both resolutions. For the entire plume, the superfine resolution increases the maximum O3 concentration 3% but only decreases the maximum Ox concentration 0.2%. The two grid sizes produce approximately equal Ox mass but by different reaction pathways. Derived sensitivity to oxides of nitrogen (NOx) and VOC emissions suggests resolution-specific sensitivity to NOx and VOC emissions. Different sensitivity to emissions will result in different O3 responses to subsequently encountered emissions (within the city or downwind). Sensitivity of O3 to emission changes also results in different simulated O3 responses to the same control strategies. Sensitivity of O3 to NOx and VOC emission changes is attributed to finer resolved Eulerian grid and finer resolved NOx emissions. Urban NOx concentration gradients are often caused by roadway mobile sources that would not typically be addressed with Plume-in-Grid models. This study shows that grid cell size (an artifact of modeling) influences simulated control strategies and could bias regulatory decisions. Understanding the dynamics of VOC plume dependence on grid size is the first step toward providing more detailed guidance for resolution. These results underscore VOC and NOx resolution interdependencies best addressed by finer resolution. On the basis of these results, the authors suggest a need for quantitative metrics for horizontal grid resolution in future model guidance.

Mesoscale data assimilation for a local severe rainfall event with the NHM-LETKF system

NASA Astrophysics Data System (ADS)

Kunii, M.

2013-12-01

This study aims to improve forecasts of local severe weather events through data assimilation and ensemble forecasting approaches. Here, the local ensemble transform Kalman filter (LETKF) is implemented with the Japan Meteorological Agency's nonhydrostatic model (NHM). The newly developed NHM-LETKF contains an adaptive inflation scheme and a spatial covariance localization scheme with physical distance. One-way nested analysis in which a finer-resolution LETKF is conducted by using the outputs of an outer model also becomes feasible. These new contents should enhance the potential of the LETKF for convective scale events. The NHM-LETKF is applied to a local severe rainfall event in Japan in 2012. Comparison of the root mean square errors between the model first guess and analysis reveals that the system assimilates observations appropriately. Analysis ensemble spreads indicate a significant increase around the time torrential rainfall occurred, which would imply an increase in the uncertainty of environmental fields. Forecasts initialized with LETKF analyses successfully capture intense rainfalls, suggesting that the system can work effectively for local severe weather. Investigation of probabilistic forecasts by ensemble forecasting indicates that this could become a reliable data source for decision making in the future. A one-way nested data assimilation scheme is also tested. The experiment results demonstrate that assimilation with a finer-resolution model provides an advantage in the quantitative precipitation forecasting of local severe weather conditions.

Nested hyper-resolution modeling of urban areas for the National Water Model - The Dallas-Fort Worth Testbed

NASA Astrophysics Data System (ADS)

Noh, S. J.; Kim, S.; Habibi, H.; Seo, D. J.; Welles, E.; Philips, B.; Adams, E.; Smith, M. B.; Wells, E.

2017-12-01

With the development of the National Water Model (NWM), the NWS has made a step-change advance in operational water forecasting by enabling high-resolution hydrologic modeling across the US. As a part of a separate initiative to enhance flash flood forecasting and inundation mapping capacity, the NWS has been mandated to provide forecasts at even finer spatiotemporal resolutions when and where such information is demanded. In this presentation, we describe implementation of the NWM at a hyper resolution over a nested domain. We use WRF-Hydro as the core model but at significantly higher resolutions with scale-commensurate model parameters. The demonstration domain is multiple urban catchments within the Cities of Arlington and Grand Prairie in the Dallas-Fort Worth Metroplex. This area is susceptible to urban flooding due to the hydroclimatology coupled with large impervious cover. The nested model is based on hyper-resolution terrain data to resolve significant land surface features such as streets and large man-made structures, and forced by the high-resolution radar-based quantitative precipitation information. In this presentation, we summarize progress and preliminary results and share issues and challenges.

Bringing the Coastal Zone into Finer Focus

NASA Astrophysics Data System (ADS)

Guild, L. S.; Hooker, S. B.; Kudela, R. M.; Morrow, J. H.; Torres-Perez, J. L.; Palacios, S. L.; Negrey, K.; Dungan, J. L.

2015-12-01

Measurements over extents from submeter to 10s of meters are critical science requirements for the design and integration of remote sensing instruments for coastal zone research. Various coastal ocean phenomena operate at different scales (e.g. meters to kilometers). For example, river plumes and algal blooms have typical extents of 10s of meters and therefore can be resolved with satellite data, however, shallow benthic ecosystem (e.g., coral, seagrass, and kelp) biodiversity and change are best studied at resolutions of submeter to meter, below the pixel size of typical satellite products. The delineation of natural phenomena do not fit nicely into gridded pixels and the coastal zone is complicated by mixed pixels at the land-sea interface with a range of bio-optical signals from terrestrial and water components. In many standard satellite products, these coastal mixed pixels are masked out because they confound algorithms for the ocean color parameter suite. In order to obtain data at the land/sea interface, finer spatial resolution satellite data can be achieved yet spectral resolution is sacrificed. This remote sensing resolution challenge thwarts the advancement of research in the coastal zone. Further, remote sensing of benthic ecosystems and shallow sub-surface phenomena are challenged by the requirements to sense through the sea surface and through a water column with varying light conditions from the open ocean to the water's edge. For coastal waters, >80% of the remote sensing signal is scattered/absorbed due to the atmospheric constituents, sun glint from the sea surface, and water column components. In addition to in-water measurements from various platforms (e.g., ship, glider, mooring, and divers), low altitude aircraft outfitted with high quality bio-optical radiometer sensors and targeted channels matched with in-water sensors and higher altitude platform sensors for ocean color products, bridge the sea-truth measurements to the pixels acquired from satellite and high altitude platforms. We highlight a novel NASA airborne calibration, validation, and research capability for addressing the coastal remote sensing resolution challenge.

Post-Disturbance Stability of Fish Assemblages Measured at Coarse Taxonomic Resolution Masks Change at Finer Scales.

PubMed

Ceccarelli, Daniela M; Emslie, Michael J; Richards, Zoe T

2016-01-01

Quantifying changes to coral reef fish assemblages in the wake of cyclonic disturbances is challenging due to spatial variability of damage inherent in such events. Often, fish abundance appears stable at one spatial scale (e.g. reef-wide), but exhibits substantial change at finer scales (e.g. site-specific decline or increase). Taxonomic resolution also plays a role; overall stability at coarse taxonomic levels (e.g. family) may mask species-level turnover. Here we document changes to reef fish communities after severe Tropical Cyclone Ita crossed Lizard Island, Great Barrier Reef. Coral and reef fish surveys were conducted concurrently before and after the cyclone at four levels of exposure to the prevailing weather. Coral cover declined across all exposures except sheltered sites, with the largest decline at exposed sites. There was no significant overall reduction in the total density, biomass and species richness of reef fishes between 2011 and 2015, but individual fish taxa (families and species) changed in complex and unpredictable ways. For example, more families increased in density and biomass than decreased following Cyclone Ita, particularly at exposed sites whilst more fish families declined at lagoon sites even though coral cover did not decline. All sites lost biomass of several damselfish species, and at most sites there was an increase in macroinvertivores and grazers. Overall, these results suggest that the degree of change measured at coarse taxonomic levels masked high species-level turnover, although other potential explanations include that there was no impact of the storm, fish assemblages were impacted but underwent rapid recovery or that there is a time lag before the full impacts become apparent. This study confirms that in high-complexity, high diversity ecosystems such as coral reefs, species level analyses are essential to adequately capture the consequences of disturbance events.

Post-Disturbance Stability of Fish Assemblages Measured at Coarse Taxonomic Resolution Masks Change at Finer Scales

PubMed Central

Ceccarelli, Daniela M.

2016-01-01

Quantifying changes to coral reef fish assemblages in the wake of cyclonic disturbances is challenging due to spatial variability of damage inherent in such events. Often, fish abundance appears stable at one spatial scale (e.g. reef-wide), but exhibits substantial change at finer scales (e.g. site-specific decline or increase). Taxonomic resolution also plays a role; overall stability at coarse taxonomic levels (e.g. family) may mask species-level turnover. Here we document changes to reef fish communities after severe Tropical Cyclone Ita crossed Lizard Island, Great Barrier Reef. Coral and reef fish surveys were conducted concurrently before and after the cyclone at four levels of exposure to the prevailing weather. Coral cover declined across all exposures except sheltered sites, with the largest decline at exposed sites. There was no significant overall reduction in the total density, biomass and species richness of reef fishes between 2011 and 2015, but individual fish taxa (families and species) changed in complex and unpredictable ways. For example, more families increased in density and biomass than decreased following Cyclone Ita, particularly at exposed sites whilst more fish families declined at lagoon sites even though coral cover did not decline. All sites lost biomass of several damselfish species, and at most sites there was an increase in macroinvertivores and grazers. Overall, these results suggest that the degree of change measured at coarse taxonomic levels masked high species-level turnover, although other potential explanations include that there was no impact of the storm, fish assemblages were impacted but underwent rapid recovery or that there is a time lag before the full impacts become apparent. This study confirms that in high-complexity, high diversity ecosystems such as coral reefs, species level analyses are essential to adequately capture the consequences of disturbance events. PMID:27285160

Environmental Gap Analysis to Prioritize Conservation Efforts in Eastern Africa

PubMed Central

van Breugel, Paulo; Kindt, Roeland; Lillesø, Jens-Peter Barnekow; van Breugel, Michiel

2015-01-01

Countries in eastern Africa have set aside significant proportions of their land for protection. But are these areas representative of the diverse range of species and habitats found in the region? And do conservation efforts include areas where the state of biodiversity is likely to deteriorate without further interventions? Various studies have addressed these questions at global and continental scales. However, meaningful conservation decisions are required at finer geographical scales. To operate more effectively at the national level, finer scale baseline data on species and on higher levels of biological organization such as the eco-regions are required, among other factors. Here we adopted a recently developed high-resolution potential natural vegetation (PNV) map for eastern Africa as a baseline to more effectively identify conservation priorities. We examined how well different potential natural vegetations (PNVs) are represented in the protected area (PA) network of eastern Africa and used a multivariate environmental similarity index to evaluate biases in PA versus PNV coverage. We additionally overlaid data of anthropogenic factors that potentially influence the natural vegetation to assess the level of threat to different PNVs. Our results indicate substantial differences in the conservation status of PNVs. In addition, particular PNVs in which biodiversity protection and ecological functions are at risk due to human influences are revealed. The data and approach presented here provide a step forward in developing more transparent and better informed translation from global priorities to regional or national implementation in eastern Africa, and are valid for other geographic regions. PMID:25855968

3D Printing Variable Stiffness Foams Using Viscous Thread Instability

NASA Astrophysics Data System (ADS)

Lipton, Jeffrey I.; Lipson, Hod

2016-08-01

Additive manufacturing of cellular structures has numerous applications ranging from fabrication of biological scaffolds and medical implants, to mechanical weight reduction and control over mechanical properties. Various additive manufacturing processes have been used to produce open regular cellular structures limited only by the resolution of the printer. These efforts have focused on printing explicitly designed cells or explicitly planning offsets between strands. Here we describe a technique for producing cellular structures implicitly by inducing viscous thread instability when extruding material. This process allows us to produce complex cellular structures at a scale that is finer than the native resolution of the printer. We demonstrate tunable effective elastic modulus and density that span two orders of magnitude. Fine grained cellular structures allow for fabrication of foams for use in a wide range of fields ranging from bioengineering, to robotics to food printing.

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

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.

Multi-scale monitoring of landscape change after the 2011 tsunami

NASA Astrophysics Data System (ADS)

Hara, K.; Zhao, Y.; Harada, I.; Tomita, M.; Park, J.; Jung, E.; Kamagata, N.; Hirabuki, Y.

2015-04-01

The Great East Japan Earthquake (magnitude 9.0; occurred on 11th March 2011) and subsequent huge tsunami caused widespread damage along the Pacific Ocean coast of eastern Honshu, Japan. This research utilizes multi-resolution remote sensing images to clarify the impact on landscapes caused by this disaster, and also to monitor the subsequent survival and recovery process in the Sendai Bay region. The coastal landscape in the target area features a narrow strip of coastal sand barrier, historically stabilized by planted pine groves; backed by a low-lying plain that has traditionally been diked and converted to irrigated rice paddies. Farmsteads on the flat alluvial plain are surrounded by groves called "Igune", consisting primarily of conifers. MODIS data (250 m resolution) were employed to map the overall extent of inundation and damage on the regional landscape scale. The major damage caused by the tsunami, destruction of coastal pine forests and inundation or rice paddies on the plain, was identified at this level. Progressively finer scale analysis were then implemented using SPOT/HRG-2 (10 m resolution) data; GeoEye-1 fine resolution data (0.5 m) and very fine resolution aerial photographs (10 cm) and LiDAR. These results demonstrated the minute details of the damage and recovery process. Some patches of pine forest, for example, were seen to have survived, and some coastal plant communities were already recovering only a year after the disaster. Continuous monitoring using field work and remote sensing is required for balanced regional strategies that provide for economic and social recovery and as well as restoration of vegetation, biodiversity and vital ecosystem services.

Development and Application of a Soil Moisture Downscaling Method for Mobility Assessment

DTIC Science & Technology

2011-05-01

instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send...REPORT Development and Application of a Soil Moisture Downscaling Method for Mobility Assessment 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Soil...cells). Thus, a method is required to downscale intermediate-resolution patterns to finer resolutions. Fortunately, fine-resolution variations in

Regional Climate Simulation with a Variable Resolution Stretched Grid GCM: The Regional Down-Scaling Effects

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Suarez, Max; Sawyer, William; Govindaraju, Ravi C.

1999-01-01

The results obtained with the variable resolution stretched grid (SG) GEOS GCM (Goddard Earth Observing System General Circulation Models) are discussed, with the emphasis on the regional down-scaling effects and their dependence on the stretched grid design and parameters. A variable resolution SG-GCM and SG-DAS using a global stretched grid with fine resolution over an area of interest, is a viable new approach to REGIONAL and subregional CLIMATE studies and applications. The stretched grid approach is an ideal tool for representing regional to global scale interactions. It is an alternative to the widely used nested grid approach introduced a decade ago as a pioneering step in regional climate modeling. The GEOS SG-GCM is used for simulations of the anomalous U.S. climate events of 1988 drought and 1993 flood, with enhanced regional resolution. The height low level jet, precipitation and other diagnostic patterns are successfully simulated and show the efficient down-scaling over the area of interest the U.S. An imitation of the nested grid approach is performed using the developed SG-DAS (Data Assimilation System) that incorporates the SG-GCM. The SG-DAS is run with withholding data over the area of interest. The design immitates the nested grid framework with boundary conditions provided from analyses. No boundary condition buffer is needed for the case due to the global domain of integration used for the SG-GCM and SG-DAS. The experiments based on the newly developed versions of the GEOS SG-GCM and SG-DAS, with finer 0.5 degree (and higher) regional resolution, are briefly discussed. The major aspects of parallelization of the SG-GCM code are outlined. The KEY OBJECTIVES of the study are: 1) obtaining an efficient DOWN-SCALING over the area of interest with fine and very fine resolution; 2) providing CONSISTENT interactions between regional and global scales including the consistent representation of regional ENERGY and WATER BALANCES; 3) providing a high computational efficiency for future SG-GCM and SG-DAS versions using PARALLEL codes.

Estimation of Actual Crop ET of Paddy Using the Energy Balance Model SMARET and Validation with Field Water Balance Measurements and a Crop Growth Model (ORYZA)

NASA Astrophysics Data System (ADS)

Nallasamy, N. D.; Muraleedharan, B. V.; Kathirvel, K.; Narasimhan, B.

2014-12-01

Sustainable management of water resources requires reliable estimates of actual evapotranspiration (ET) at fine spatial and temporal resolution. This is significant in the case of rice based irrigation systems, one of the major consumers of surface water resources and where ET forms a major component of water consumption. However huge tradeoff in the spatial and temporal resolution of satellite images coupled with lack of adequate number of cloud free images within a growing season act as major constraints in deriving ET at fine spatial and temporal resolution using remote sensing based energy balance models. The scale at which ET is determined is decided by the spatial and temporal scale of Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), which form inputs to energy balance models. In this context, the current study employed disaggregation algorithms (NL-DisTrad and DisNDVI) to generate time series of LST and NDVI images at fine resolution. The disaggregation algorithms aimed at generating LST and NDVI at finer scale by integrating temporal information from concurrent coarse resolution data and spatial information from a single fine resolution image. The temporal frequency of the disaggregated images is further improved by employing composite images of NDVI and LST in the spatio-temporal disaggregation method. The study further employed half-hourly incoming surface insolation and outgoing long wave radiation obtained from the Indian geostationary satellite (Kalpana-1) to convert the instantaneous ET into daily ET and subsequently to the seasonal ET, thereby improving the accuracy of ET estimates. The estimates of ET were validated with field based water balance measurements carried out in Gadana, a subbasin predominated by rice paddy fields, located in Tamil Nadu, India.

Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, S.; Kim, H.; Choi, M.; Kim, K.

2016-12-01

Estimating spatiotemporal variation of soil moisture is crucial to hydrological applications such as flood, drought, and near real-time climate forecasting. Recent advances in space-based passive microwave measurements allow the frequent monitoring of the surface soil moisture at a global scale and downscaling approaches have been applied to improve the spatial resolution of passive microwave products available at local scale applications. However, most downscaling methods using optical and thermal dataset, are valid only in cloud-free conditions; thus renewed downscaling method under all sky condition is necessary for the establishment of spatiotemporal continuity of datasets at fine resolution. In present study Support Vector Machine (SVM) technique was utilized to downscale a satellite-based soil moisture retrievals. The 0.1 and 0.25-degree resolution of daily Land Parameter Retrieval Model (LPRM) L3 soil moisture datasets from Advanced Microwave Scanning Radiometer 2 (AMSR2) were disaggregated over Northeast Asia in 2015. Optically derived estimates of surface temperature (LST), normalized difference vegetation index (NDVI), and its cloud products were obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) for the purpose of downscaling soil moisture in finer resolution under all sky condition. Furthermore, a comparison analysis between in situ and downscaled soil moisture products was also conducted for quantitatively assessing its accuracy. Results showed that downscaled soil moisture under all sky condition not only preserves the quality of AMSR2 LPRM soil moisture at 1km resolution, but also attains higher spatial data coverage. From this research we expect that time continuous monitoring of soil moisture at fine scale regardless of weather conditions would be available.

A review of potential image fusion methods for remote sensing-based irrigation management: Part II

USDA-ARS?s Scientific Manuscript database

Satellite-based sensors provide data at either greater spectral and coarser spatial resolutions, or lower spectral and finer spatial resolutions due to complementary spectral and spatial characteristics of optical sensor systems. In order to overcome this limitation, image fusion has been suggested ...

Pore-scale dynamics of salt transport in drying porous media

NASA Astrophysics Data System (ADS)

Shokri, N.

2013-12-01

Understanding the physics of water evaporation from saline porous media is important in many hydrological processes such as land-atmosphere interactions, water management, vegetation, soil salinity, and mineral-fluid interactions. We applied synchrotron x-ray micro-tomography to investigate the pore-scale dynamics of dissolved salt distribution in a three dimensional drying saline porous media using a cylindrical plastic column (15 mm in height and 8 mm in diameter) packed with sand particles saturated with CaI2 solution (5% concentration by mass) with a spatial and temporal resolution of 12 microns and 30 min, respectively. Every time the drying sand column was set to be imaged, two different images were recorded using distinct synchrotron X-rays energies immediately above (33.2690 keV) and below (33.0690 keV) the K-edge value of Iodine (33.1694 keV). Taking the difference between pixel gray values enabled us to delineate the spatial and temporal distribution of CaI2 concentration at pore scale. The experiment was continued for 12 hours. Results indicate that during early stages of evaporation, air preferentially invades large pores at the surface while finer pores remain saturated and connected to the wet zone at bottom via capillary-induced liquid flow. Consequently, the salt concentration increases preferentially in finer pores where evaporation occurs. The Peclet number (describing the competition between convection and diffusion) was greater than one in our experiment resulting in higher salt concentrations closer to the evaporation surface indicating a convection-driven process. The obtained salt profiles were used to evaluate the numerical solution of the convection-diffusion equation (CDE). Results show that the macro-scale CDE could capture the overall trend of the measured salt profiles but fail to produce the exact slope of the profiles. Our results shed new insight on the physics of salt transport and its complex dynamics in drying porous media and establish synchrotron x-ray micro-tomography as an effective tool to investigate the dynamics of dissolved salt transport in porous media with high spatial and temporal resolutions.

Solutions Network Formulation Report. Visible/Infrared Imager/Radiometer Suite and Landsat Data Continuity Mission Simulated Data Products for the Great Lakes Basin Ecological Team

NASA Technical Reports Server (NTRS)

Estep, Leland

2007-01-01

The proposed solution would simulate VIIRS and LDCM sensor data for use in the USGS/USFWS GLBET DST. The VIIRS sensor possesses a spectral range that provides water-penetrating bands that could be used to assess water clarity on a regional spatial scale. The LDCM sensor possesses suitable spectral bands in a range of wavelengths that could be used to map water quality at finer spatial scales relative to VIIRS. Water quality, alongshore sediment transport and pollutant discharge tracking into the Great Lakes system are targeted as the primary products to be developed. A principal benefit of water quality monitoring via satellite imagery is its economy compared to field-data collection methods. Additionally, higher resolution satellite imagery provides a baseline dataset(s) against which later imagery can be overlaid in GIS-based DST programs. Further, information derived from higher resolution satellite imagery can be used to address public concerns and to confirm environmental compliance. The candidate solution supports the Public Health, Coastal Management, and Water Management National Applications.

A generalized formulation for downscaling data based on Fourier Transform and inversion: Mathematical rationale and application to the Max-Planck-Institute aerosol climatology data

NASA Astrophysics Data System (ADS)

Zhang, Taiping; Stackhouse, Paul W.; Gupta, Shashi K.; Cox, Stephen J.; Mikovitz, J. Colleen

2017-02-01

Occasionally, a need arises to downscale a time series of data from a coarse temporal resolution to a finer one, a typical example being from monthly means to daily means. For this case, daily means derived as such are used as inputs of climatic or atmospheric models so that the model results may exhibit variance on the daily time scale and retain the monthly mean of the original data set without an abrupt change from the end of one month to the beginning of the next. Different methods have been developed which often need assumptions, free parameters and the solution of simultaneous equations. Here we derive a generalized formulation by means of Fourier transform and inversion so that it can be used to directly compute daily means from a series of an arbitrary number of monthly means. The formulation can be used to transform any coarse temporal resolution to a finer one. From the derived results, the original data can be recovered almost identically. As a real application, we use this method to derive the daily counterpart of the MAC-v1 aerosol climatology that provides monthly mean aerosol properties for 18 shortwave bands and 12 longwave bands for the years from 1860 to 2100. The derived daily means are to be used as inputs of the shortwave and longwave algorithms of the NASA GEWEX SRB project.

Application of Geostatistical Simulation to Enhance Satellite Image Products

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David

2004-01-01

With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

3D Printing Variable Stiffness Foams Using Viscous Thread Instability

PubMed Central

Lipton, Jeffrey I.; Lipson, Hod

2016-01-01

Additive manufacturing of cellular structures has numerous applications ranging from fabrication of biological scaffolds and medical implants, to mechanical weight reduction and control over mechanical properties. Various additive manufacturing processes have been used to produce open regular cellular structures limited only by the resolution of the printer. These efforts have focused on printing explicitly designed cells or explicitly planning offsets between strands. Here we describe a technique for producing cellular structures implicitly by inducing viscous thread instability when extruding material. This process allows us to produce complex cellular structures at a scale that is finer than the native resolution of the printer. We demonstrate tunable effective elastic modulus and density that span two orders of magnitude. Fine grained cellular structures allow for fabrication of foams for use in a wide range of fields ranging from bioengineering, to robotics to food printing. PMID:27503148

Landslide Hazard from Coupled Inherent and Dynamic Probabilities

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.; Nudurupati, S. S.

2015-12-01

Landslide hazard research has typically been conducted independently from hydroclimate research. We sought to unify these two lines of research to provide regional scale landslide hazard information for risk assessments and resource management decision-making. Our approach couples an empirical inherent landslide probability, based on a frequency ratio analysis, with a numerical dynamic probability, generated by combining subsurface water recharge and surface runoff from the Variable Infiltration Capacity (VIC) macro-scale land surface hydrologic model with a finer resolution probabilistic slope stability model. Landslide hazard mapping is advanced by combining static and dynamic models of stability into a probabilistic measure of geohazard prediction in both space and time. This work will aid resource management decision-making in current and future landscape and climatic conditions. The approach is applied as a case study in North Cascade National Park Complex in northern Washington State.

A Geosynchronous Lidar System for Atmospheric Winds and Moisture Measurements

NASA Technical Reports Server (NTRS)

Emmitt, G. D.

2001-01-01

An observing system comprised of two lidars in geosychronous orbit would enable the synoptic and meso-scale measurement of atmospheric winds and moisture both of which are key first-order variables of the Earth's weather equation. Simultaneous measurement of these parameters at fast revisit rates promises large advancements in our weather prediction skills. Such capabilities would be unprecedented and a) yield greatly improved and finer resolution initial conditions for models, b) make existing costly and cumbersome measurement approaches obsolete, and c) obviate the use of numerical techniques needed to correct data obtained using present observing systems. Additionally, simultaneous synoptic wind and moisture observations would lead to improvements in model parameterizations, and in our knowledge of small-scale weather processes. Technology and science data product assessments are ongoing. Results will be presented during the conference.

Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching.

Treesearch

E.H. Helmer; B. Ruefenacht

2005-01-01

Cloud-free optical satellite imagery simplifies remote sensing, but land-cover phenology limits existing solutions to persistent cloudiness to compositing temporally resolute, spatially coarser imagery. Here, a new strategy for developing cloud-free imagery at finer resolution permits simple automatic change detection. The strategy uses regression trees to predict...

A neural-network approach to robotic control

NASA Technical Reports Server (NTRS)

Graham, D. P. W.; Deleuterio, G. M. T.

1993-01-01

An artificial neural-network paradigm for the control of robotic systems is presented. The approach is based on the Cerebellar Model Articulation Controller created by James Albus and incorporates several extensions. First, recognizing the essential structure of multibody equations of motion, two parallel modules are used that directly reflect the dynamical characteristics of multibody systems. Second, the architecture of the proposed network is imbued with a self-organizational capability which improves efficiency and accuracy. Also, the networks can be arranged in hierarchical fashion with each subsequent network providing finer and finer resolution.

Towards a High-Resolution Global Inundation Delineation Dataset

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.

2011-12-01

Although their importance for biodiversity, flow regulation and ecosystem service provision is widely recognized, wetlands and temporarily inundated landscapes remain poorly mapped globally because of their inherent elusive nature. Inventorying of wetland resources has been identified in international agreements as an essential component of appropriate conservation efforts and management initiatives of these threatened ecosystems. However, despite recent advances in remote sensing surface water monitoring, current inventories of surface water variations remain incomplete at the regional-to-global scale due to methodological limitations restricting truly global application. Remote sensing wetland applications such as SAR L-band are particularly constrained by image availability and heterogeneity of acquisition dates, while coarse resolution passive microwave and multi-sensor methods cannot discriminate distinct surface water bodies. As a result, the most popular global wetland dataset remains to this day the Global Lake & Wetland Database (Lehner and Doll, 2004) a spatially inconsistent database assembled from various existing data sources. The approach taken in this project circumvents the limitations of current global wetland monitoring methods by combining globally available topographic and hydrographic data to downscale coarse resolution global inundation data (Prigent et al., 2007) and thus create a superior inundation delineation map product. The developed procedure downscales inundation data from the coarse resolution (~27km) of current passive microwave sensors to the finer spatial resolution (~500m) of the topographic and hydrographic layers of HydroSHEDS' data suite (Lehner et al., 2006), while retaining the high temporal resolution of the multi-sensor inundation dataset. From the downscaling process emerges new information on the specific location of inundation, but also on its frequency and duration. The downscaling algorithm employs a decision tree classifier trained on regional remote sensing wetland maps, to derive inundation probability followed by a seeded region growing segmentation process to redistribute the inundated area at the finer resolution. Assessment of the algorithm's performance is accomplished by evaluating the level of agreement between its outputted downscaled inundation maps and existing regional remote sensing inundation delineation. Upon completion, this project's will offer a dynamic globally seamless inundation map at an unprecedented spatial and temporal scale, which will provide the baseline inventory long requested by the research community, and will open the door to a wide array of possible conservation and hydrological modeling applications which were until now data-restricted. Literature Lehner, B., K. Verdin, and A. Jarvis. 2008. New global hydrography derived from spaceborne elevation data. Eos 89, no. 10. Lehner, B, and P Doll. 2004. Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology 296, no. 1-4: 1-22. Prigent, C., F. Papa, F. Aires, W. B. Rossow, and E. Matthews. 2007. Global inundation dynamics inferred from multiple satellite observations, 1993-2000. Journal of Geophysical Research 112, no. D12: 1-13.

Does resolution of flow field observation influence apparent habitat use and energy expenditure in juvenile coho salmon?

NASA Astrophysics Data System (ADS)

Tullos, D. D.; Walter, C.; Dunham, J.

2016-12-01

This study investigated how the resolution of observation influences interpretation of how fish, juvenile Coho Salmon (Oncorhynchus kisutch), exploit the hydraulic environment in streams. Our objectives were to evaluate how spatial resolution of the flow field observation influenced: 1) the velocities considered to be representative of habitat units; 2) patterns of use of the hydraulic environment by fish; and 3) estimates of energy expenditure. We addressed these objectives using observations within a 1:1 scale physical model of a full-channel log jam in an outdoor experimental stream. Velocities were measured with Acoustic Doppler Velocimetry at a 10 cm grid spacing, whereas fish locations and tailbeat frequencies were documented over time using underwater videogrammetry. Results highlighted that resolution of observation did impact perceived habitat use and energy expenditure, as did the location of measurement within habitat units and the use of averaging to summarize velocities within a habitat unit. In this experiment, the range of velocities and energy expenditure estimates increased with coarsening resolution, reducing the likelihood of measuring the velocities locally experienced by fish. In addition, the coarser resolutions contributed to fish appearing to select velocities that were higher than what was measured at finer resolutions. These findings indicate the need for careful attention to and communication of resolution of observation in investigating the hydraulic environment and in determining the habitat needs and bioenergetics of aquatic biota.

Spatial consistency of chinook salmon redd distribution within and among years in the Cowlitz River, Washington

USGS Publications Warehouse

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.

Evaluation of remotely sensed actual evapotranspiration data for modeling small scale irrigation in Ethiopia.

NASA Astrophysics Data System (ADS)

Taddele, Y. D.; Ayana, E.; Worqlul, A. W.; Srinivasan, R.; Gerik, T.; Clarke, N.

2017-12-01

The research presented in this paper is conducted in Ethiopia, which is located in the horn of Africa. Ethiopian economy largely depends on rainfed agriculture, which employs 80% of the labor force. The rainfed agriculture is frequently affected by droughts and dry spells. Small scale irrigation is considered as the lifeline for the livelihoods of smallholder farmers in Ethiopia. Biophysical models are highly used to determine the agricultural production, environmental sustainability, and socio-economic outcomes of small scale irrigation in Ethiopia. However, detailed spatially explicit data is not adequately available to calibrate and validate simulations from biophysical models. The Soil and Water Assessment Tool (SWAT) model was setup using finer resolution spatial and temporal data. The actual evapotranspiration (AET) estimation from the SWAT model was compared with two remotely sensed data, namely the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectrometer (MODIS). The performance of the monthly satellite data was evaluated with correlation coefficient (R2) over the different land use groups. The result indicated that over the long term and monthly the AVHRR AET captures the pattern of SWAT simulated AET reasonably well, especially on agricultural dominated landscapes. A comparison between SWAT simulated AET and AVHRR AET provided mixed results on grassland dominated landscapes and poor agreement on forest dominated landscapes. Results showed that the AVHRR AET products showed superior agreement with the SWAT simulated AET than MODIS AET. This suggests that remotely sensed products can be used as valuable tool in properly modeling small scale irrigation.

Detecting vortices in superconductors: Extracting one-dimensional topological singularities from a discretized complex scalar field

DOE PAGES

Phillips, Carolyn L.; Peterka, Tom; Karpeyev, Dmitry; ...

2015-02-20

In type II superconductors, the dynamics of superconducting vortices determine their transport properties. In the Ginzburg-Landau theory, vortices correspond to topological defects in the complex order parameter. Extracting their precise positions and motion from discretized numerical simulation data is an important, but challenging, task. In the past, vortices have mostly been detected by analyzing the magnitude of the complex scalar field representing the order parameter and visualized by corresponding contour plots and isosurfaces. However, these methods, primarily used for small-scale simulations, blur the fine details of the vortices, scale poorly to large-scale simulations, and do not easily enable isolating andmore » tracking individual vortices. In this paper, we present a method for exactly finding the vortex core lines from a complex order parameter field. With this method, vortices can be easily described at a resolution even finer than the mesh itself. The precise determination of the vortex cores allows the interplay of the vortices inside a model superconductor to be visualized in higher resolution than has previously been possible. Finally, by representing the field as the set of vortices, this method also massively reduces the data footprint of the simulations and provides the data structures for further analysis and feature tracking.« less

Global terrain classification using Multiple-Error-Removed Improved-Terrain (MERIT) to address susceptibility of landslides and other geohazards

NASA Astrophysics Data System (ADS)

Iwahashi, J.; Yamazaki, D.; Matsuoka, M.; Thamarux, P.; Herrick, J.; Yong, A.; Mital, U.

2017-12-01

A seamless model of landform classifications with regional accuracy will be a powerful platform for geophysical studies that forecast geologic hazards. Spatial variability as a function of landform on a global scale was captured in the automated classifications of Iwahashi and Pike (2007) and additional developments are presented here that incorporate more accurate depictions using higher-resolution elevation data than the original 1-km scale Shuttle Radar Topography Mission digital elevation model (DEM). We create polygon-based terrain classifications globally by using the 280-m DEM interpolated from the Multi-Error-Removed Improved-Terrain DEM (MERIT; Yamazaki et al., 2017). The multi-scale pixel-image analysis method, known as Multi-resolution Segmentation (Baatz and Schäpe, 2000), is first used to classify the terrains based on geometric signatures (slope and local convexity) calculated from the 280-m DEM. Next, we apply the machine learning method of "k-means clustering" to prepare the polygon-based classification at the globe-scale using slope, local convexity and surface texture. We then group the divisions with similar properties by hierarchical clustering and other statistical analyses using geological and geomorphological data of the area where landslides and earthquakes are frequent (e.g. Japan and California). We find the 280-m DEM resolution is only partially sufficient for classifying plains. We nevertheless observe that the categories correspond to reported landslide and liquefaction features at the global scale, suggesting that our model is an appropriate platform to forecast ground failure. To predict seismic amplification, we estimate site conditions using the time-averaged shear-wave velocity in the upper 30-m (VS30) measurements compiled by Yong et al. (2016) and the terrain model developed by Yong (2016; Y16). We plan to test our method on finer resolution DEMs and report our findings to obtain a more globally consistent terrain model as there are known errors in DEM derivatives at higher-resolutions. We expect the improvement in DEM resolution (4 times greater detail) and the combination of regional and global coverage will yield a consistent dataset of polygons that have the potential to improve relations to the Y16 estimates significantly.

An efficient pseudomedian filter for tiling microrrays.

PubMed

Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B

2007-06-07

Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at http://tiling.gersteinlab.org/pseudomedian/.

An efficient pseudomedian filter for tiling microrrays

PubMed Central

Royce, Thomas E; Carriero, Nicholas J; Gerstein, Mark B

2007-01-01

Background Tiling microarrays are becoming an essential technology in the functional genomics toolbox. They have been applied to the tasks of novel transcript identification, elucidation of transcription factor binding sites, detection of methylated DNA and several other applications in several model organisms. These experiments are being conducted at increasingly finer resolutions as the microarray technology enjoys increasingly greater feature densities. The increased densities naturally lead to increased data analysis requirements. Specifically, the most widely employed algorithm for tiling array analysis involves smoothing observed signals by computing pseudomedians within sliding windows, a O(n2logn) calculation in each window. This poor time complexity is an issue for tiling array analysis and could prove to be a real bottleneck as tiling microarray experiments become grander in scope and finer in resolution. Results We therefore implemented Monahan's HLQEST algorithm that reduces the runtime complexity for computing the pseudomedian of n numbers to O(nlogn) from O(n2logn). For a representative tiling microarray dataset, this modification reduced the smoothing procedure's runtime by nearly 90%. We then leveraged the fact that elements within sliding windows remain largely unchanged in overlapping windows (as one slides across genomic space) to further reduce computation by an additional 43%. This was achieved by the application of skip lists to maintaining a sorted list of values from window to window. This sorted list could be maintained with simple O(log n) inserts and deletes. We illustrate the favorable scaling properties of our algorithms with both time complexity analysis and benchmarking on synthetic datasets. Conclusion Tiling microarray analyses that rely upon a sliding window pseudomedian calculation can require many hours of computation. We have eased this requirement significantly by implementing efficient algorithms that scale well with genomic feature density. This result not only speeds the current standard analyses, but also makes possible ones where many iterations of the filter may be required, such as might be required in a bootstrap or parameter estimation setting. Source code and executables are available at . PMID:17555595

Enhanced-Resolution Satellite Microwave Brightness Temperature Records for Mapping Boreal-Arctic Landscape Freeze-Thaw Heterogeneity

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.

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space.

PubMed

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2016-04-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement, and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

Objects Grouping for Segmentation of Roads Network in High Resolution Images of Urban Areas

NASA Astrophysics Data System (ADS)

Maboudi, M.; Amini, J.; Hahn, M.

2016-06-01

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors - as the main source of large scale mapping applications - was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of "Object-based Image Analysis (OBIA)" as an alternative to pixel-based image analysis methods. Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

The expanding scope of air pollution monitoring can facilitate sustainable development.

PubMed

Knox, Andrew; Mykhaylova, Natalia; Evans, Greg J; Lee, Colin J; Karney, Bryan; Brook, Jeffrey R

2013-03-15

This paper explores technologies currently expanding the physical scope of air pollution monitoring and their potential contributions to the assessment of sustainable development. This potential lies largely in the ability of these technologies to address issues typically on the fringe of the air pollution agenda. Air pollution monitoring tends to be primarily focused on human health, and largely neglects other aspects of sustainable development. Sensor networks, with their relatively inexpensive monitoring nodes, allow for monitoring with finer spatiotemporal resolution. This resolution can support more conclusive studies of air pollution's effect on socio-ecological justice and human quality of life. Satellite observation of air pollution allows for wider geographical scope, and in doing so can facilitate studies of air pollution's effects on natural capital and ecosystem resilience. Many air pollution-related aspects of the sustainability of development in human systems are not being given their due attention. Opportunities exist for air pollution monitoring to attend more to these issues. Improvements to the resolution and scale of monitoring make these opportunities realizable. Copyright © 2012 Elsevier B.V. All rights reserved.

Segmented Domain Decomposition Multigrid For 3-D Turbomachinery Flows

NASA Technical Reports Server (NTRS)

Celestina, M. L.; Adamczyk, J. J.; Rubin, S. G.

2001-01-01

A Segmented Domain Decomposition Multigrid (SDDMG) procedure was developed for three-dimensional viscous flow problems as they apply to turbomachinery flows. The procedure divides the computational domain into a coarse mesh comprised of uniformly spaced cells. To resolve smaller length scales such as the viscous layer near a surface, segments of the coarse mesh are subdivided into a finer mesh. This is repeated until adequate resolution of the smallest relevant length scale is obtained. Multigrid is used to communicate information between the different grid levels. To test the procedure, simulation results will be presented for a compressor and turbine cascade. These simulations are intended to show the ability of the present method to generate grid independent solutions. Comparisons with data will also be presented. These comparisons will further demonstrate the usefulness of the present work for they allow an estimate of the accuracy of the flow modeling equations independent of error attributed to numerical discretization.

Geographical ecology of the palms (Arecaceae): determinants of diversity and distributions across spatial scales

PubMed Central

Eiserhardt, Wolf L.; Svenning, Jens-Christian; Kissling, W. Daniel; Balslev, Henrik

2011-01-01

Background The palm family occurs in all tropical and sub-tropical regions of the world. Palms are of high ecological and economical importance, and display complex spatial patterns of species distributions and diversity. Scope This review summarizes empirical evidence for factors that determine palm species distributions, community composition and species richness such as the abiotic environment (climate, soil chemistry, hydrology and topography), the biotic environment (vegetation structure and species interactions) and dispersal. The importance of contemporary vs. historical impacts of these factors and the scale at which they function is discussed. Finally a hierarchical scale framework is developed to guide predictor selection for future studies. Conclusions Determinants of palm distributions, composition and richness vary with spatial scale. For species distributions, climate appears to be important at landscape and broader scales, soil, topography and vegetation at landscape and local scales, hydrology at local scales, and dispersal at all scales. For community composition, soil appears important at regional and finer scales, hydrology, topography and vegetation at landscape and local scales, and dispersal again at all scales. For species richness, climate and dispersal appear to be important at continental to global scales, soil at landscape and broader scales, and topography at landscape and finer scales. Some scale–predictor combinations have not been studied or deserve further attention, e.g. climate on regional to finer scales, and hydrology and topography on landscape and broader scales. The importance of biotic interactions – apart from general vegetation structure effects – for the geographic ecology of palms is generally underexplored. Future studies should target scale–predictor combinations and geographic domains not studied yet. To avoid biased inference, one should ideally include at least all predictors previously found important at the spatial scale of investigation. PMID:21712297

A dynamic subgrid-scale parameterization of the effective wall stress in atmospheric boundary layer flows over multiscale, fractal-like surfaces

NASA Astrophysics Data System (ADS)

Anderson, William; Meneveau, Charles

2010-05-01

A dynamic subgrid-scale (SGS) parameterization for hydrodynamic surface roughness is developed for large-eddy simulation (LES) of atmospheric boundary layer (ABL) flow over multiscale, fractal-like surfaces. The model consists of two parts. First, a baseline model represents surface roughness at horizontal length-scales that can be resolved in the LES. This model takes the form of a force using a prescribed drag coefficient. This approach is tested in LES of flow over cubes, wavy surfaces, and ellipsoidal roughness elements for which there are detailed experimental data available. Secondly, a dynamic roughness model is built, accounting for SGS surface details of finer resolution than the LES grid width. The SGS boundary condition is based on the logarithmic law of the wall, where the unresolved roughness of the surface is modeled as the product of local root-mean-square (RMS) of the unresolved surface height and an unknown dimensionless model coefficient. This coefficient is evaluated dynamically by comparing the plane-average hydrodynamic drag at two resolutions (grid- and test-filter scale, Germano et al., 1991). The new model is tested on surfaces generated through superposition of random-phase Fourier modes with prescribed, power-law surface-height spectra. The results show that the method yields convergent results and correct trends. Limitations and further challenges are highlighted. Supported by the US National Science Foundation (EAR-0609690).

A high-resolution global-scale groundwater model

NASA Astrophysics Data System (ADS)

de Graaf, I. E. M.; Sutanudjaja, E. H.; van Beek, L. P. H.; Bierkens, M. F. P.

2015-02-01

Groundwater is the world's largest accessible source of fresh water. It plays a vital role in satisfying basic needs for drinking water, agriculture and industrial activities. During times of drought groundwater sustains baseflow to rivers and wetlands, thereby supporting ecosystems. Most global-scale hydrological models (GHMs) do not include a groundwater flow component, mainly due to lack of geohydrological data at the global scale. For the simulation of lateral flow and groundwater head dynamics, a realistic physical representation of the groundwater system is needed, especially for GHMs that run at finer resolutions. In this study we present a global-scale groundwater model (run at 6' resolution) using MODFLOW to construct an equilibrium water table at its natural state as the result of long-term climatic forcing. The used aquifer schematization and properties are based on available global data sets of lithology and transmissivities combined with the estimated thickness of an upper, unconfined aquifer. This model is forced with outputs from the land-surface PCRaster Global Water Balance (PCR-GLOBWB) model, specifically net recharge and surface water levels. A sensitivity analysis, in which the model was run with various parameter settings, showed that variation in saturated conductivity has the largest impact on the groundwater levels simulated. Validation with observed groundwater heads showed that groundwater heads are reasonably well simulated for many regions of the world, especially for sediment basins (R2 = 0.95). The simulated regional-scale groundwater patterns and flow paths demonstrate the relevance of lateral groundwater flow in GHMs. Inter-basin groundwater flows can be a significant part of a basin's water budget and help to sustain river baseflows, especially during droughts. Also, water availability of larger aquifer systems can be positively affected by additional recharge from inter-basin groundwater flows.

Wind turbine wake interactions at field scale: An LES study of the SWiFT facility

NASA Astrophysics Data System (ADS)

Yang, Xiaolei; Boomsma, Aaron; Barone, Matthew; Sotiropoulos, Fotis

2014-06-01

The University of Minnesota Virtual Wind Simulator (VWiS) code is employed to simulate turbine/atmosphere interactions in the Scaled Wind Farm Technology (SWiFT) facility developed by Sandia National Laboratories in Lubbock, TX, USA. The facility presently consists of three turbines and the simulations consider the case of wind blowing from South such that two turbines are in the free stream and the third turbine in the direct wake of one upstream turbine with separation of 5 rotor diameters. Large-eddy simulation (LES) on two successively finer grids is carried out to examine the sensitivity of the computed solutions to grid refinement. It is found that the details of the break-up of the tip vortices into small-scale turbulence structures can only be resolved on the finer grid. It is also shown that the power coefficient CP of the downwind turbine predicted on the coarse grid is somewhat higher than that obtained on the fine mesh. On the other hand, the rms (root-mean-square) of the CP fluctuations are nearly the same on both grids, although more small-scale turbulence structures are resolved upwind of the downwind turbine on the finer grid.

The impact of resolution on the dynamics of the martian global atmosphere: Varying resolution studies with the MarsWRF GCM

NASA Astrophysics Data System (ADS)

Toigo, Anthony D.; Lee, Christopher; Newman, Claire E.; Richardson, Mark I.

2012-09-01

We investigate the sensitivity of the circulation and thermal structure of the martian atmosphere to numerical model resolution in a general circulation model (GCM) using the martian implementation (MarsWRF) of the planetWRF atmospheric model. We provide a description of the MarsWRF GCM and use it to study the global atmosphere at horizontal resolutions from 7.5° × 9° to 0.5° × 0.5°, encompassing the range from standard Mars GCMs to global mesoscale modeling. We find that while most of the gross-scale features of the circulation (the rough location of jets, the qualitative thermal structure, and the major large-scale features of the surface level winds) are insensitive to horizontal resolution over this range, several major features of the circulation are sensitive in detail. The northern winter polar circulation shows the greatest sensitivity, showing a continuous transition from a smooth polar winter jet at low resolution, to a distinct vertically “split” jet as resolution increases. The separation of the lower and middle atmosphere polar jet occurs at roughly 10 Pa, with the split jet structure developing in concert with the intensification of meridional jets at roughly 10 Pa and above 0.1 Pa. These meridional jets appear to represent the separation of lower and middle atmosphere mean overturning circulations (with the former being consistent with the usual concept of the “Hadley cell”). Further, the transition in polar jet structure is more sensitive to changes in zonal than meridional horizontal resolution, suggesting that representation of small-scale wave-mean flow interactions is more important than fine-scale representation of the meridional thermal gradient across the polar front. Increasing the horizontal resolution improves the match between the modeled thermal structure and the Mars Climate Sounder retrievals for northern winter high latitudes. While increased horizontal resolution also improves the simulation of the northern high latitudes at equinox, even the lowest model resolution considered here appears to do a good job for the southern winter and southern equinoctial pole (although in detail some discrepancies remain). These results suggest that studies of the northern winter jet (e.g., transient waves and cyclogenesis) will be more sensitive to global model resolution that those of the south (e.g., the confining dynamics of the southern polar vortex relevant to studies of argon transport). For surface winds, the major effect of increased horizontal resolution is in the superposition of circulations forced by local-scale topography upon the large-scale surface wind patterns. While passive predictions of dust lifting are generally insensitive to model horizontal resolution when no lifting threshold is considered, increasing the stress threshold produces significantly more lifting in higher resolution simulations with the generation of finer-scale, higher-stress winds due primarily to better-resolved topography. Considering the positive feedbacks expected for radiatively active dust lifting, we expect this bias to increase when such feedbacks are permitted.

A non-parametric, supervised classification of vegetation types on the Kaibab National Forest using decision trees

Treesearch

Suzanne M. Joy; R. M. Reich; Richard T. Reynolds

2003-01-01

Traditional land classification techniques for large areas that use Landsat Thematic Mapper (TM) imagery are typically limited to the fixed spatial resolution of the sensors (30m). However, the study of some ecological processes requires land cover classifications at finer spatial resolutions. We model forest vegetation types on the Kaibab National Forest (KNF) in...

On the effects of scale for ecosystem services mapping

USGS Publications Warehouse

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

On the Effects of Scale for Ecosystem Services Mapping

PubMed Central

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability. PMID:25549256

On the effects of scale for ecosystem services mapping.

PubMed

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

A Simple Downscaling Algorithm for Remotely Sensed Land Surface Temperature

NASA Astrophysics Data System (ADS)

Sandholt, I.; Nielsen, C.; Stisen, S.

2009-05-01

The method is illustrated using a combination of MODIS NDVI data with a spatial resolution of 250m and 3 Km Meteosat Second Generation SEVIRI LST data. Geostationary Earth Observation data carry a large potential for assessment of surface state variables. Not the least the European Meteosat Second Generation platform with its SEVIRI sensor is well suited for studies of the dynamics of land surfaces due to its high temporal frequency (15 minutes) and its red, Near Infrared (NIR) channels that provides vegetation indices, and its two split window channels in the thermal infrared for assessment of Land Surface Temperature (LST). For some applications the spatial resolution in geostationary data is too coarse. Due to the low statial resolution of 4.8 km at nadir for the SEVIRI sensor, a means of providing sub pixel information is sought for. By combining and properly scaling two types of satellite images, namely data from the MODIS sensor onboard the polar orbiting platforms TERRA and AQUA and the coarse resolution MSG-SEVIRI, we exploit the best from two worlds. The vegetation index/surface temperature space has been used in a vast number of studies for assessment of air temperature, soil moisture, dryness indices, evapotranspiration and for studies of land use change. In this paper, we present an improved method to derive a finer resolution Land Surface Temperature (LST). A new, deterministic scaling method has been applied, and is compared to existing deterministic downscaling methods based on LST and NDVI. We also compare our results from in situ measurements of LST from the Dahra test site in West Africa.

Insights into the physico-chemical evolution of pyrogenic organic carbon emissions from biomass burning using coupled Lagrangian-Eulerian simulations

NASA Astrophysics Data System (ADS)

Suciu, L. G.; Griffin, R. J.; Masiello, C. A.

2017-12-01

Wildfires and prescribed burning are important sources of particulate and gaseous pyrogenic organic carbon (PyOC) emissions to the atmosphere. These emissions impact atmospheric chemistry, air quality and climate, but the spatial and temporal variabilities of these impacts are poorly understood, primarily because small and fresh fire plumes are not well predicted by three-dimensional Eulerian chemical transport models due to their coarser grid size. Generally, this results in underestimation of downwind deposition of PyOC, hydroxyl radical reactivity, secondary organic aerosol formation and ozone (O3) production. However, such models are very good for simulation of multiple atmospheric processes that could affect the lifetimes of PyOC emissions over large spatiotemporal scales. Finer resolution models, such as Lagrangian reactive plumes models (or plume-in-grid), could be used to trace fresh emissions at the sub-grid level of the Eulerian model. Moreover, Lagrangian plume models need background chemistry predicted by the Eulerian models to accurately simulate the interactions of the plume material with the background air during plume aging. Therefore, by coupling the two models, the physico-chemical evolution of the biomass burning plumes can be tracked from local to regional scales. In this study, we focus on the physico-chemical changes of PyOC emissions from sub-grid to grid levels using an existing chemical mechanism. We hypothesize that finer scale Lagrangian-Eulerian simulations of several prescribed burns in the U.S. will allow more accurate downwind predictions (validated by airborne observations from smoke plumes) of PyOC emissions (i.e., submicron particulate matter, organic aerosols, refractory black carbon) as well as O3 and other trace gases. Simulation results could be used to optimize the implementation of additional PyOC speciation in the existing chemical mechanism.

Landslide Hazard Probability Derived from Inherent and Dynamic Determinants

NASA Astrophysics Data System (ADS)

Strauch, Ronda; Istanbulluoglu, Erkan

2016-04-01

Landslide hazard research has typically been conducted independently from hydroclimate research. We unify these two lines of research to provide regional scale landslide hazard information for risk assessments and resource management decision-making. Our approach combines an empirical inherent landslide probability with a numerical dynamic probability, generated by combining routed recharge from the Variable Infiltration Capacity (VIC) macro-scale land surface hydrologic model with a finer resolution probabilistic slope stability model run in a Monte Carlo simulation. Landslide hazard mapping is advanced by adjusting the dynamic model of stability with an empirically-based scalar representing the inherent stability of the landscape, creating a probabilistic quantitative measure of geohazard prediction at a 30-m resolution. Climatology, soil, and topography control the dynamic nature of hillslope stability and the empirical information further improves the discriminating ability of the integrated model. This work will aid resource management decision-making in current and future landscape and climatic conditions. The approach is applied as a case study in North Cascade National Park Complex, a rugged terrain with nearly 2,700 m (9,000 ft) of vertical relief, covering 2757 sq km (1064 sq mi) in northern Washington State, U.S.A.

A MULTISCALE FRAMEWORK FOR THE STOCHASTIC ASSIMILATION AND MODELING OF UNCERTAINTY ASSOCIATED NCF COMPOSITE MATERIALS

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

Mehrez, Loujaine; Ghanem, Roger; McAuliffe, Colin

multiscale framework to construct stochastic macroscopic constitutive material models is proposed. A spectral projection approach, specifically polynomial chaos expansion, has been used to construct explicit functional relationships between the homogenized properties and input parameters from finer scales. A homogenization engine embedded in Multiscale Designer, software for composite materials, has been used for the upscaling process. The framework is demonstrated using non-crimp fabric composite materials by constructing probabilistic models of the homogenized properties of a non-crimp fabric laminate in terms of the input parameters together with the homogenized properties from finer scales.

High-resolution photography of clouds from the surface: Retrieval of optical depth of thin clouds down to centimeter scales: High-Resolution Photography of Clouds

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

Schwartz, Stephen E.; Huang, Dong; Vladutescu, Daniela Viviana

This article describes the approach and presents initial results, for a period of several minutes in north central Oklahoma, of an examination of clouds by high resolution digital photography from the surface looking vertically upward. A commercially available camera having 35-mm equivalent focal length up to 1200 mm (nominal resolution as fine as 6 µrad, which corresponds to 9 mm for cloud height 1.5 km) is used to obtain a measure of zenith radiance of a 30 m × 30 m domain as a two-dimensional image consisting of 3456 × 3456 pixels (12 million pixels). Downwelling zenith radiance varies substantiallymore » within single images and between successive images obtained at 4-s intervals. Variation in zenith radiance found on scales down to about 10 cm is attributed to variation in cloud optical depth (COD). Attention here is directed primarily to optically thin clouds, COD less than about 2. A radiation transfer model used to relate downwelling zenith radiance to COD and to relate the counts in the camera image to zenith radiance, permits determination of COD on a pixel-by-pixel basis. COD for thin clouds determined in this way exhibits considerable variation, for example, an order of magnitude within 15 m, a factor of 2 within 4 m, and 25% (0.12 to 0.15) over 14 cm. In conclusion, this approach, which examines cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opens new avenues for examination of cloud structure and evolution.« less

High-resolution photography of clouds from the surface: Retrieval of optical depth of thin clouds down to centimeter scales: High-Resolution Photography of Clouds

DOE PAGES

Schwartz, Stephen E.; Huang, Dong; Vladutescu, Daniela Viviana

2017-03-08

This article describes the approach and presents initial results, for a period of several minutes in north central Oklahoma, of an examination of clouds by high resolution digital photography from the surface looking vertically upward. A commercially available camera having 35-mm equivalent focal length up to 1200 mm (nominal resolution as fine as 6 µrad, which corresponds to 9 mm for cloud height 1.5 km) is used to obtain a measure of zenith radiance of a 30 m × 30 m domain as a two-dimensional image consisting of 3456 × 3456 pixels (12 million pixels). Downwelling zenith radiance varies substantiallymore » within single images and between successive images obtained at 4-s intervals. Variation in zenith radiance found on scales down to about 10 cm is attributed to variation in cloud optical depth (COD). Attention here is directed primarily to optically thin clouds, COD less than about 2. A radiation transfer model used to relate downwelling zenith radiance to COD and to relate the counts in the camera image to zenith radiance, permits determination of COD on a pixel-by-pixel basis. COD for thin clouds determined in this way exhibits considerable variation, for example, an order of magnitude within 15 m, a factor of 2 within 4 m, and 25% (0.12 to 0.15) over 14 cm. In conclusion, this approach, which examines cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opens new avenues for examination of cloud structure and evolution.« less

Exploring the Utility of the Planned CYGNSS Mission for Investigating the Initiation and Development of the Madden-Julian Oscillation

NASA Technical Reports Server (NTRS)

Lang, Timothy; Mecikalski, John; Li, Xuanli; Chronis, Themis; Brewer, Alan; Churnside, James; Rutledge, Steve

2014-01-01

CYGNSS is a planned constellation consisting of multiple micro-satellites that leverage the Global Positioning System (GPS) to provide rapidly updated, high resolution (approx. 15-50 km, approx. 4 h) surface wind speeds (via bi-static scatterometry) over the tropical oceans in any weather condition, including heavy rainfall. The approach of the work to be presented at this conference is to utilize a limited-domain, cloud-system resolving model (Weather Research and Forecasting or WRF) and its attendant data assimilation scheme (Three-Dimensional Variational Assimilation or 3DVAR) to investigate the utility of the CYGNSS mission for helping characterize key convectiveto- mesoscale processes - such as surface evaporation, moisture advection and convergence, and upscale development of precipitation systems - that help drive the initiation and development of the Madden-Julian Oscillation (MJO) in the equatorial Indian Ocean. The proposed work will focus on three scientific objectives. Objective 1 is to produce a high-resolution surface wind dataset resolution (approx. 0.5 h, approx. 1-4 km) for multiple MJO onsets using WRF-assimilated winds and other data from the DYNAmics of the MJO (DYNAMO) field campaign, which took place during October 2011 - March 2012. Objective 2 is to study the variability of surface winds during MJO onsets at temporal and spatial scales of finer resolution than future CYGNSS data. The goal is to understand how sub-CYGNSS-resolution processes will shape the observations made by the satellite constellation. Objective 3 is to ingest simulated CYGNSS data into the WRF model in order to perform observing system simulation experiments (OSSEs). These will be used to test and quantify the potential beneficial effects provided by CYGNSS, particularly for characterizing the physical processes driving convective organization and upscale development during the initiation and development of the MJO. The proposed research is ideal for answering important questions about the CYGNSS mission, such as the representativeness of surface wind retrievals in the context of the complex airflow processes that occur during heavy precipitation, as well as the tradeoffs in retrieval accuracy that result from finer spatial resolution of the CYGNSS winds versus increased errors/noisiness in those data. Research plans and initial progress toward these objectives will be presented.

Evaluating DEM conditioning techniques, elevation source data, and grid resolution for field-scale hydrological parameter extraction

NASA Astrophysics Data System (ADS)

Woodrow, Kathryn; Lindsay, John B.; Berg, Aaron A.

2016-09-01

Although digital elevation models (DEMs) prove useful for a number of hydrological applications, they are often the end result of numerous processing steps that each contains uncertainty. These uncertainties have the potential to greatly influence DEM quality and to further propagate to DEM-derived attributes including derived surface and near-surface drainage patterns. This research examines the impacts of DEM grid resolution, elevation source data, and conditioning techniques on the spatial and statistical distribution of field-scale hydrological attributes for a 12,000 ha watershed of an agricultural area within southwestern Ontario, Canada. Three conditioning techniques, including depression filling (DF), depression breaching (DB), and stream burning (SB), were examined. The catchments draining to each boundary of 7933 agricultural fields were delineated using the surface drainage patterns modeled from LiDAR data, interpolated to a 1 m, 5 m, and 10 m resolution DEMs, and from a 10 m resolution photogrammetric DEM. The results showed that variation in DEM grid resolution resulted in significant differences in the spatial and statistical distributions of contributing areas and the distributions of downslope flowpath length. Degrading the grid resolution of the LiDAR data from 1 m to 10 m resulted in a disagreement in mapped contributing areas of between 29.4% and 37.3% of the study area, depending on the DEM conditioning technique. The disagreements among the field-scale contributing areas mapped from the 10 m LiDAR DEM and photogrammetric DEM were large, with nearly half of the study area draining to alternate field boundaries. Differences in derived contributing areas and flowpaths among various conditioning techniques increased substantially at finer grid resolutions, with the largest disagreement among mapped contributing areas occurring between the 1 m resolution DB DEM and the SB DEM (37% disagreement) and the DB-DF comparison (36.5% disagreement in mapped areas). These results demonstrate that the decision to use one DEM conditioning technique over another, and the constraints of available DEM data resolution and source, can greatly impact the modeled surface drainage patterns at the scale of individual fields. This work has significance for applications that attempt to optimize best-management practices (BMPs) for reducing soil erosion and runoff contamination within agricultural watersheds.

Cross-scale interactions affect tree growth and intrinsic water ...

EPA Pesticide Factsheets

1. We investigated the potential of cross-scale interactions to affect the outcome of density reduction in a large-scale silvicultural experiment. 2. We measured tree growth and intrinsic water-use efficiency (iWUE) based on stable carbon isotopes (13C) to investigate the impacts of thinning across a range of progressively finer spatial scales: site, stand, hillslope position, and neighborhood position. In particular, we focused on the influence of thinning beyond the boundaries of thinned stands to include impacts on downslope and neighboring stands across sites varying in soil moisture. 3. Trees at the wet site responded to thinning with increased growth when compared with trees at the dry site. Additionally, trees in thinned stands at the dry site responded with increased iWUE while trees in thinned stands at the wet site showed no difference in iWUE compared to unthinned stands. 4. We hypothesized that water is not the primary limiting factor for growth at our sites, but that thinning released other resources, such as growing space or nutrients to drive the growth response. At progressively finer spatial scales we found that the responses of trees was not driven by hillslope location (i.e., downslope of thinning) but to changes in local neighborhood tree density. 5. The results of this study demonstrated that water can be viewed as an “agent” that allows us to investigate cross-scale interactions as it links coarse to finer spatial scales and vice ver

Large-Eddy Simulations of Atmospheric Flows Over Complex Terrain Using the Immersed-Boundary Method in the Weather Research and Forecasting Model

NASA Astrophysics Data System (ADS)

Ma, Yulong; Liu, Heping

2017-12-01

Atmospheric flow over complex terrain, particularly recirculation flows, greatly influences wind-turbine siting, forest-fire behaviour, and trace-gas and pollutant dispersion. However, there is a large uncertainty in the simulation of flow over complex topography, which is attributable to the type of turbulence model, the subgrid-scale (SGS) turbulence parametrization, terrain-following coordinates, and numerical errors in finite-difference methods. Here, we upgrade the large-eddy simulation module within the Weather Research and Forecasting model by incorporating the immersed-boundary method into the module to improve simulations of the flow and recirculation over complex terrain. Simulations over the Bolund Hill indicate improved mean absolute speed-up errors with respect to previous studies, as well an improved simulation of the recirculation zone behind the escarpment of the hill. With regard to the SGS parametrization, the Lagrangian-averaged scale-dependent Smagorinsky model performs better than the classic Smagorinsky model in reproducing both velocity and turbulent kinetic energy. A finer grid resolution also improves the strength of the recirculation in flow simulations, with a higher horizontal grid resolution improving simulations just behind the escarpment, and a higher vertical grid resolution improving results on the lee side of the hill. Our modelling approach has broad applications for the simulation of atmospheric flows over complex topography.

Multimodel Simulation of Water Flow: Uncertainty Analysis

USDA-ARS?s Scientific Manuscript database

Simulations of soil water flow require measurements of soil hydraulic properties which are particularly difficult at the field scale. Laboratory measurements provide hydraulic properties at scales finer than the field scale, whereas pedotransfer functions (PTFs) integrate information on hydraulic pr...

Does resolution of flow field observation influence apparent habitat use and energy expenditure in juvenile coho salmon?

USGS Publications Warehouse

Tullos, Desiree D.; Walter, Cara; Dunham, Jason B.

2016-01-01

This study investigated how the resolution of observation influences interpretation of how fish, juvenile Coho Salmon (Oncorhynchus kisutch), exploit the hydraulic environment in streams. Our objectives were to evaluate how spatial resolution of the flow field observation influenced: (1) the velocities considered to be representative of habitat units; (2) patterns of use of the hydraulic environment by fish; and (3) estimates of energy expenditure. We addressed these objectives using observations within a 1:1 scale physical model of a full-channel log jam in an outdoor experimental stream. Velocities were measured with Acoustic Doppler Velocimetry at a 10 cm grid spacing, whereas fish locations and tailbeat frequencies were documented over time using underwater videogrammetry. Results highlighted that resolution of observation did impact perceived habitat use and energy expenditure, as did the location of measurement within habitat units and the use of averaging to summarize velocities within a habitat unit. In this experiment, the range of velocities and energy expenditure estimates increased with coarsening resolution (grid spacing from 10 to 100 cm), reducing the likelihood of measuring the velocities locally experienced by fish. In addition, the coarser resolutions contributed to fish appearing to select velocities that were higher than what was measured at finer resolutions. These findings indicate the need for careful attention to and communication of resolution of observation in investigating the hydraulic environment and in determining the habitat needs and bioenergetics of aquatic biota.

Wavelet-based de-noising algorithm for images acquired with parallel magnetic resonance imaging (MRI).

PubMed

Delakis, Ioannis; Hammad, Omer; Kitney, Richard I

2007-07-07

Wavelet-based de-noising has been shown to improve image signal-to-noise ratio in magnetic resonance imaging (MRI) while maintaining spatial resolution. Wavelet-based de-noising techniques typically implemented in MRI require that noise displays uniform spatial distribution. However, images acquired with parallel MRI have spatially varying noise levels. In this work, a new algorithm for filtering images with parallel MRI is presented. The proposed algorithm extracts the edges from the original image and then generates a noise map from the wavelet coefficients at finer scales. The noise map is zeroed at locations where edges have been detected and directional analysis is also used to calculate noise in regions of low-contrast edges that may not have been detected. The new methodology was applied on phantom and brain images and compared with other applicable de-noising techniques. The performance of the proposed algorithm was shown to be comparable with other techniques in central areas of the images, where noise levels are high. In addition, finer details and edges were maintained in peripheral areas, where noise levels are low. The proposed methodology is fully automated and can be applied on final reconstructed images without requiring sensitivity profiles or noise matrices of the receiver coils, therefore making it suitable for implementation in a clinical MRI setting.

Sedimentary architecture of the Shaler outcrop, Gale Crater, Mars: paleoenvironmental and sediment transport implications

NASA Astrophysics Data System (ADS)

Gupta, S.; Edgar, L. A.; Rubin, D. M.; Lewis, K. W.; Kocurek, G.; Anderson, R. B.; Bell, J. F.; Dromart, G.; Edgett, K. S.; Grotzinger, J. P.; Hardgrove, C. J.; Kah, L. C.; Leveille, R. J.; Malin, M.; Mangold, N.; Milliken, R.; Minitti, M. E.; Muller, J.; Rice, M. S.; Rowland, S. K.; Schieber, J.; Stack, K.; Sumner, D. Y.; Team, M.

2013-12-01

Sedimentary rocks are archives of ancient depositional processes and environments on planetary surfaces. Reconstructing such processes and environments requires observations of sedimentary structures and architecture (the large-scale geometry and organisation of sedimentary bedsets). We report the analysis of the distinct Shaler outcrop, a prominent stratified unit located between the Bathurst Inlet outcrop and the floor of Yellowknife bay. The Shaler outcrop is an ~1 m thick stratal unit that spans approximately 30 m outcrop in length, and was examined by Curiosity on sols 120-121 and more recently on sols 309-324. Detailed stereo observations of the outcrop across most of its entire lateral extent were made using Navigation and Mast Cameras. These data permit detailed analysis of stratal geometries, distribution of sedimentary structures, and broad grain size trends. Overall the Shaler outcrop comprises a heterogeneous assemblage of interstratified platy sandstones separated by recessive, likely finer-grained beds. Coarser-grained beds are characterised by decimeter-scale trough cross-bedding. The north-eastern section of the outcrop shows greater abundance of interstratified sandstones and finer-grained beds. The southwestern section is characterised by darker bedsets that are likely coarser grained interstratified with finer-grained sandstones. The darker bedsets appear to comprise stacked trough-cross stratified bedsets. Finer-grained recessive intervals are not apparent in this section. The presence and scale of trough cross-stratification indicates that sediment was transported by the migration of sinuous crested dunes. Bedding geometries indicate sub-critical angles of climb. We examine the large-scale bedset architecture to evaluate the original depositional geometry of the Shaler sedimentary system, and consider its plausible depositional processes and paleoenvironmental setting. Finally, we consider its relationship to the sedimentary succession exposed in the Yellowknife bay region.

Sensitivity to grid resolution in the ability of a chemical transport model to simulate observed oxidant chemistry under high-isoprene conditions

NASA Astrophysics Data System (ADS)

Yu, Karen; Jacob, Daniel J.; Fisher, Jenny A.; Kim, Patrick S.; Marais, Eloise A.; Miller, Christopher C.; Travis, Katherine R.; Zhu, Lei; Yantosca, Robert M.; Sulprizio, Melissa P.; Cohen, Ron C.; Dibb, Jack E.; Fried, Alan; Mikoviny, Tomas; Ryerson, Thomas B.; Wennberg, Paul O.; Wisthaler, Armin

2016-04-01

Formation of ozone and organic aerosol in continental atmospheres depends on whether isoprene emitted by vegetation is oxidized by the high-NOx pathway (where peroxy radicals react with NO) or by low-NOx pathways (where peroxy radicals react by alternate channels, mostly with HO2). We used mixed layer observations from the SEAC4RS aircraft campaign over the Southeast US to test the ability of the GEOS-Chem chemical transport model at different grid resolutions (0.25° × 0.3125°, 2° × 2.5°, 4° × 5°) to simulate this chemistry under high-isoprene, variable-NOx conditions. Observations of isoprene and NOx over the Southeast US show a negative correlation, reflecting the spatial segregation of emissions; this negative correlation is captured in the model at 0.25° × 0.3125° resolution but not at coarser resolutions. As a result, less isoprene oxidation takes place by the high-NOx pathway in the model at 0.25° × 0.3125° resolution (54 %) than at coarser resolution (59 %). The cumulative probability distribution functions (CDFs) of NOx, isoprene, and ozone concentrations show little difference across model resolutions and good agreement with observations, while formaldehyde is overestimated at coarse resolution because excessive isoprene oxidation takes place by the high-NOx pathway with high formaldehyde yield. The good agreement of simulated and observed concentration variances implies that smaller-scale non-linearities (urban and power plant plumes) are not important on the regional scale. Correlations of simulated vs. observed concentrations do not improve with grid resolution because finer modes of variability are intrinsically more difficult to capture. Higher model resolution leads to decreased conversion of NOx to organic nitrates and increased conversion to nitric acid, with total reactive nitrogen oxides (NOy) changing little across model resolutions. Model concentrations in the lower free troposphere are also insensitive to grid resolution. The overall low sensitivity of modeled concentrations to grid resolution implies that coarse resolution is adequate when modeling continental boundary layer chemistry for global applications.

Evaluation of precipitation trends from high-resolution satellite precipitation products over Mainland China

NASA Astrophysics Data System (ADS)

Chen, Fengrui; Gao, Yongqi

2018-01-01

Many studies have reported the excellent ability of high-resolution satellite precipitation products (0.25° or finer) to capture the spatial distribution of precipitation. However, it is not known whether the precipitation trends derived from them are reliable. For the first time, we have evaluated the annual and seasonal precipitation trends from two typical sources of high-resolution satellite-gauge products, TRMM 3B43 and PERSIANN-CDR, using rain gauge observations over China, and they were also compared with those from gauge-only products (0.25° and 0.5° precipitation products, hereafter called CN25 and CN50). The evaluation focused mainly on the magnitude, significance, sign, and relative order of the precipitation trends, and was conducted at gridded and regional scales. The following results were obtained: (1) at the gridded scale, neither satellite-gauge products precisely measure the magnitude of precipitation trends but they do reproduce their sign and relative order; regarding capturing the significance of trends, they exhibit relatively acceptable performance only over regions with a sufficient amount of significant precipitation trends; (2) at the regional scale, both satellite-gauge products generally provide reliable precipitation trends, although they do not reproduce the magnitude of trends in winter precipitation; and (3) overall, CN50 and TRMM 3B43 outperform others in reproducing all four aspects of the precipitation trends. Compared with CN25, PERSIANN-CDR performs better in determining the magnitude of precipitation trends but marginally worse in reproducing their sign and relative order; moreover, both of them are at a level in capturing the significance of precipitation trends.

Scanning Backscatter Lidar Observations for Characterizing 4-D Cloud and Aerosol Fields to Improve Radiative Transfer Parameterizations

NASA Technical Reports Server (NTRS)

Schwemmer, Geary K.; Miller, David O.

2005-01-01

Clouds have a powerful influence on atmospheric radiative transfer and hence are crucial to understanding and interpreting the exchange of radiation between the Earth's surface, the atmosphere, and space. Because clouds are highly variable in space, time and physical makeup, it is important to be able to observe them in three dimensions (3-D) with sufficient resolution that the data can be used to generate and validate parameterizations of cloud fields at the resolution scale of global climate models (GCMs). Simulation of photon transport in three dimensionally inhomogeneous cloud fields show that spatial inhomogeneities tend to decrease cloud reflection and absorption and increase direct and diffuse transmission, Therefore it is an important task to characterize cloud spatial structures in three dimensions on the scale of GCM grid elements. In order to validate cloud parameterizations that represent the ensemble, or mean and variance of cloud properties within a GCM grid element, measurements of the parameters must be obtained on a much finer scale so that the statistics on those measurements are truly representative. High spatial sampling resolution is required, on the order of 1 km or less. Since the radiation fields respond almost instantaneously to changes in the cloud field, and clouds changes occur on scales of seconds and less when viewed on scales of approximately 100m, the temporal resolution of cloud properties should be measured and characterized on second time scales. GCM time steps are typically on the order of an hour, but in order to obtain sufficient statistical representations of cloud properties in the parameterizations that are used as model inputs, averaged values of cloud properties should be calculated on time scales on the order of 10-100 s. The Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) provides exceptional temporal (100 ms) and spatial (30 m) resolution measurements of aerosol and cloud backscatter in three dimensions. HARLIE was used in a ground-based configuration in several recent field campaigns. Principal data products include aerosol backscatter profiles, boundary layer heights, entrainment zone thickness, cloud fraction as a function of altitude and horizontal wind vector profiles based on correlating the motions of clouds and aerosol structures across portions of the scan. Comparisons will be made between various cloud detecting instruments to develop a baseline performance metric.

Still searching for the Holy Grail: on the use of effective soil parameters for Parflow-CLM.

NASA Astrophysics Data System (ADS)

Baroni, Gabriele; Schalge, Bernd; Rihani, Jehan; Attinger, Sabine

2015-04-01

In the last decades the advances in computer science have led to a growing number of coupled and distributed hydrological models based on Richards' equation. Several studies were conducted for understanding hydrological processes at different spatial and temporal scales and they showed promising uses of these types of models also in practical applications. However, these models are generally applied to scales different from that at which the equation is deduced and validated. For this reason, the models are implemented with effective soil parameters that, in principle, should preserve the water fluxes that would have been estimated assuming the finer resolution scale. In this context, the reduction in spatial discretization becomes a trade-off between complexity and performance of the model. The aim of the present contribution is to assess the performance of Parflow-CLM implemented at different spatial scales. A virtual experiment based on data available for the Neckar catchment (Germany) is used as reference at 100x100m resolution. Different upscaling rules for the soil hydraulic parameters are used for coarsening the model up to 1x1km. The analysis is carried out based on different model output e.g., river discharge, evapotranspiration, soil moisture and groundwater recharge. The effects of soil variability, correlation length and spatial distribution over the water flow direction on the simulation results are discussed. Further researches aim to quantify the related uncertainty in model output and the possibility to fill in the model structure inadequacy with data assimilation techniques.

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

NASA Astrophysics Data System (ADS)

Simmer, C.

2015-12-01

An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

The BMPix and PEAK Tools: New Methods for Automated Laminae Recognition and Counting - Application to Glacial Varves From Antarctic Marine Sediment

NASA Astrophysics Data System (ADS)

Weber, M. E.; Reichelt, L.; Kuhn, G.; Thurow, J. W.; Ricken, W.

2009-12-01

We present software-based tools for rapid and quantitative detection of sediment lamination. The BMPix tool extracts color and gray-scale curves from images at ultrahigh (pixel) resolution. The PEAK tool uses the gray-scale curve and performs, for the first time, fully automated counting of laminae based on three methods. The maximum count algorithm counts every bright peak of a couplet of two laminae (annual resolution) in a Gaussian smoothed gray-scale curve. The zero-crossing algorithm counts every positive and negative halfway-passage of the gray-scale curve through a wide moving average. Hence, the record is separated into bright and dark intervals (seasonal resolution). The same is true for the frequency truncation method, which uses Fourier transformation to decompose the gray-scale curve into its frequency components, before positive and negative passages are count. We applied the new methods successfully to tree rings and to well-dated and already manually counted marine varves from Saanich Inlet before we adopted the tools to rather complex marine laminae from the Antarctic continental margin. In combination with AMS14C dating, we found convincing evidence that the laminations from three Weddell Sea sites represent true varves that were deposited on sediment ridges over several millennia during the last glacial maximum (LGM). There are apparently two seasonal layers of terrigenous composition, a coarser-grained bright layer, and a finer-grained dark layer. The new tools offer several advantages over previous tools. The counting procedures are based on a moving average generated from gray-scale curves instead of manual counting. Hence, results are highly objective and rely on reproducible mathematical criteria. Since PEAK associates counts with a specific depth, the thickness of each year or each season is also measured which is an important prerequisite for later spectral analysis. Since all information required to conduct the analysis is displayed graphically, interactive optimization of the counting algorithms can be achieved quickly and conveniently.

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

NASA Technical Reports Server (NTRS)

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2016-01-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement (DEM), and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 meters were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

PubMed Central

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2017-01-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement, and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes. PMID:29629207

North Twin Peak in super resolution

NASA Technical Reports Server (NTRS)

1997-01-01

This pair of images shows the result of taking a sequence of 25 identical exposures from the Imager for Mars Pathfinder (IMP) of the northern Twin Peak, with small camera motions, and processing them with the Super-Resolution algorithm developed at NASA's Ames Research Center.

The upper image is a representative input image, scaled up by a factor of five, with the pixel edges smoothed out for a fair comparison. The lower image allows significantly finer detail to be resolved.

Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. JPL is an operating division of the California Institute of Technology (Caltech). The Imager for Mars Pathfinder (IMP) was developed by the University of Arizona Lunar and Planetary Laboratory under contract to JPL. Peter Smith is the Principal Investigator.

The super-resolution research was conducted by Peter Cheeseman, Bob Kanefsky, Robin Hanson, and John Stutz of NASA's Ames Research Center, Mountain View, CA. More information on this technology is available on the Ames Super Resolution home page at

http://ic-www.arc.nasa.gov/ic/projects/bayes-group/ group/super-res/

Performance measures for freight & general traffic : investigating similarities and differences using alternate data sources.

DOT National Transportation Integrated Search

2015-06-01

Recent advances in probe vehicle data collection systems have enabled monitoring traffic : conditions at finer temporal and spatial resolution. The primary objective of the current study is : to leverage these probe data sources to understand if ther...

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

NASA Astrophysics Data System (ADS)

Vennam, L. P.; Vizuete, W.; Talgo, K.; Omary, M.; Binkowski, F. S.; Xing, J.; Mathur, R.; Arunachalam, S.

2017-12-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed 1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m3) of total O3 and PM2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O3 0.69, 0.5-0.85 ppbv) and 0.5% (PM2.5 0.03, 0.01-0.05 μg/m3)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km2) and fine (36 × 36 km2) grid resolutions in NA showed 70 times and 13 times higher aviation impacts for O3 and PM2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution

PubMed Central

Vennam, L. P.; Vizuete, W.; Talgo, K.; Omary, M.; Binkowski, F. S.; Xing, J.; Mathur, R.; Arunachalam, S.

2018-01-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9–12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min–max: 0.46, 0.3–0.5 ppbv) and 0.2% (0.013, 0.004–0.02 μg/m3) of total O3 and PM2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O3 0.69, 0.5–0.85 ppbv) and 0.5% (PM2.5 0.03, 0.01–0.05 μg/m3)) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km2) and fine (36 × 36 km2) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O3 and PM2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions. PMID:29707471

Modeled Full-Flight Aircraft Emissions Impacts on Air Quality and Their Sensitivity to Grid Resolution.

PubMed

Vennam, L P; Vizuete, W; Talgo, K; Omary, M; Binkowski, F S; Xing, J; Mathur, R; Arunachalam, S

2017-01-01

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m 3 ) of total O 3 and PM 2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O 3 0.69, 0.5-0.85 ppbv) and 0.5% (PM 2.5 0.03, 0.01-0.05 μg/m 3 )) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km 2 ) and fine (36 × 36 km 2 ) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O 3 and PM 2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

Interpolation of diffusion weighted imaging datasets.

PubMed

Dyrby, Tim B; Lundell, Henrik; Burke, Mark W; Reislev, Nina L; Paulson, Olaf B; Ptito, Maurice; Siebner, Hartwig R

2014-12-01

Diffusion weighted imaging (DWI) is used to study white-matter fibre organisation, orientation and structural connectivity by means of fibre reconstruction algorithms and tractography. For clinical settings, limited scan time compromises the possibilities to achieve high image resolution for finer anatomical details and signal-to-noise-ratio for reliable fibre reconstruction. We assessed the potential benefits of interpolating DWI datasets to a higher image resolution before fibre reconstruction using a diffusion tensor model. Simulations of straight and curved crossing tracts smaller than or equal to the voxel size showed that conventional higher-order interpolation methods improved the geometrical representation of white-matter tracts with reduced partial-volume-effect (PVE), except at tract boundaries. Simulations and interpolation of ex-vivo monkey brain DWI datasets revealed that conventional interpolation methods fail to disentangle fine anatomical details if PVE is too pronounced in the original data. As for validation we used ex-vivo DWI datasets acquired at various image resolutions as well as Nissl-stained sections. Increasing the image resolution by a factor of eight yielded finer geometrical resolution and more anatomical details in complex regions such as tract boundaries and cortical layers, which are normally only visualized at higher image resolutions. Similar results were found with typical clinical human DWI dataset. However, a possible bias in quantitative values imposed by the interpolation method used should be considered. The results indicate that conventional interpolation methods can be successfully applied to DWI datasets for mining anatomical details that are normally seen only at higher resolutions, which will aid in tractography and microstructural mapping of tissue compartments. Copyright © 2014. Published by Elsevier Inc.

Impact of model resolution on simulating the water vapor transport through the central Himalayas: implication for models' wet bias over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Lin, Changgui; Chen, Deliang; Yang, Kun; Ou, Tinghai

2018-01-01

Current climate models commonly overestimate precipitation over the Tibetan Plateau (TP), which limits our understanding of past and future water balance in the region. Identifying sources of such models' wet bias is therefore crucial. The Himalayas is considered a major pathway of water vapor transport (WVT) towards the TP. Their steep terrain, together with associated small-scale processes, cannot be resolved by coarse-resolution models, which may result in excessive WVT towards the TP. This paper, therefore, investigated the resolution dependency of simulated WVT through the central Himalayas and its further impact on precipitation bias over the TP. According to a summer monsoon season of simulations conducted using the weather research forecasting (WRF) model with resolutions of 30, 10, and 2 km, the study found that finer resolutions (especially 2 km) diminish the positive precipitation bias over the TP. The higher-resolution simulations produce more precipitation over the southern Himalayan slopes and weaker WVT towards the TP, explaining the reduced wet bias. The decreased WVT is reflected mostly in the weakened wind speed, which is due to the fact that the high resolution can improve resolving orographic drag over a complex terrain and other processes associated with heterogeneous surface forcing. A significant difference was particularly found when the model resolution is changed from 30 to 10 km, suggesting that a resolution of approximately 10 km represents a good compromise between a more spatially detailed simulation of WVT and computational cost for a domain covering the whole TP.

Shallowing-upward cyclic patterns within larger-scale transgressive-regressive (T-R) sedimentary sequences, St. Peter through Decorah Formations, Ordovician, Iowa area

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

Witzke, B.J.

1993-03-01

Four large-scale (2--8 Ma) T-R sedimentary sequences of M. Ord. age (late Chaz.-Sherm.) were delimited by Witzke Kolata (1980) in the Iowa area, each bounded by local to regional unconformity/disconformity surfaces. These encompass both siliciclastic and carbonate intervals, in ascending order: (1) St. Peter-Glenwood fms., (2) Platteville Fm., (3) Decorah Fm., (4) Dunleith/upper Decorah fms. Finer-scale resolution of depth-related depositional features has led to regional recognition of smaller-scale shallowing-upward cyclicity contained within each large-scale sequence. Such smaller-scale cyclicity encompasses stratigraphic intervals of 1--10 m thickness, with estimated durations of 0.5--1.5 Ma. The St. Peter Sandst. has long been regarded asmore » a classic transgressive sheet sand. However, four discrete shallowing-upward packages characterize the St. Peter-Glenwood interval regionally (IA, MN, NB, KS), including western facies displaying coarsening-upward sandstone packages with condensed conodont-rich brown shale and phosphatic sediments in their lower part (local oolitic ironstone), commonly above pyritic hardgrounds. Regional continuity of small-scale cyclic patterns in M. Ord. strata of the Iowa area may suggest eustatic controls; this can be tested through inter-regional comparisons.« less

Multiscale registration algorithm for alignment of meshes

NASA Astrophysics Data System (ADS)

Vadde, Srikanth; Kamarthi, Sagar V.; Gupta, Surendra M.

2004-03-01

Taking a multi-resolution approach, this research work proposes an effective algorithm for aligning a pair of scans obtained by scanning an object's surface from two adjacent views. This algorithm first encases each scan in the pair with an array of cubes of equal and fixed size. For each scan in the pair a surrogate scan is created by the centroids of the cubes that encase the scan. The Gaussian curvatures of points across the surrogate scan pair are compared to find the surrogate corresponding points. If the difference between the Gaussian curvatures of any two points on the surrogate scan pair is less than a predetermined threshold, then those two points are accepted as a pair of surrogate corresponding points. The rotation and translation values between the surrogate scan pair are determined by using a set of surrogate corresponding points. Using the same rotation and translation values the original scan pairs are aligned. The resulting registration (or alignment) error is computed to check the accuracy of the scan alignment. When the registration error becomes acceptably small, the algorithm is terminated. Otherwise the above process is continued with cubes of smaller and smaller sizes until the algorithm is terminated. However at each finer resolution the search space for finding the surrogate corresponding points is restricted to the regions in the neighborhood of the surrogate points that were at found at the preceding coarser level. The surrogate corresponding points, as the resolution becomes finer and finer, converge to the true corresponding points on the original scans. This approach offers three main benefits: it improves the chances of finding the true corresponding points on the scans, minimize the adverse effects of noise in the scans, and reduce the computational load for finding the corresponding points.

Downscaling SMAP Radiometer Soil Moisture over the CONUS using Soil-Climate Information and Ensemble Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, P.; Moradkhani, H.

2017-12-01

Soil moisture contributes significantly towards the improvement of weather and climate forecast and understanding terrestrial ecosystem processes. It is known as a key hydrologic variable in the agricultural drought monitoring, flood modeling and irrigation management. While satellite retrievals can provide an unprecedented information on soil moisture at global-scale, the products are generally at coarse spatial resolutions (25-50 km2). This often hampers their use in regional or local studies, which normally require a finer resolution of the data set. This work presents a new framework based on an ensemble learning method while using soil-climate information derived from remote-sensing and ground-based observations to downscale the level 3 daily composite version (L3_SM_P) of SMAP radiometer soil moisture over the Continental U.S. (CONUS) at 1 km spatial resolution. In the proposed method, a suite of remotely sensed and in situ data sets in addition to soil texture information and topography data among others were used. The downscaled product was validated against in situ soil moisture measurements collected from a limited number of core validation sites and several hundred sparse soil moisture networks throughout the CONUS. The obtained results indicated a great potential of the proposed methodology to derive the fine resolution soil moisture information applicable for fine resolution hydrologic modeling, data assimilation and other regional studies.

Sharpening vision by adapting to flicker.

PubMed

Arnold, Derek H; Williams, Jeremy D; Phipps, Natasha E; Goodale, Melvyn A

2016-11-01

Human vision is surprisingly malleable. A static stimulus can seem to move after prolonged exposure to movement (the motion aftereffect), and exposure to tilted lines can make vertical lines seem oppositely tilted (the tilt aftereffect). The paradigm used to induce such distortions (adaptation) can provide powerful insights into the computations underlying human visual experience. Previously spatial form and stimulus dynamics were thought to be encoded independently, but here we show that adaptation to stimulus dynamics can sharpen form perception. We find that fast flicker adaptation (FFAd) shifts the tuning of face perception to higher spatial frequencies, enhances the acuity of spatial vision-allowing people to localize inputs with greater precision and to read finer scaled text, and it selectively reduces sensitivity to coarse-scale form signals. These findings are consistent with two interrelated influences: FFAd reduces the responsiveness of magnocellular neurons (which are important for encoding dynamics, but can have poor spatial resolution), and magnocellular responses contribute coarse spatial scale information when the visual system synthesizes form signals. Consequently, when magnocellular responses are mitigated via FFAd, human form perception is transiently sharpened because "blur" signals are mitigated.

Sharpening vision by adapting to flicker

PubMed Central

Arnold, Derek H.; Williams, Jeremy D.; Phipps, Natasha E.; Goodale, Melvyn A.

2016-01-01

Human vision is surprisingly malleable. A static stimulus can seem to move after prolonged exposure to movement (the motion aftereffect), and exposure to tilted lines can make vertical lines seem oppositely tilted (the tilt aftereffect). The paradigm used to induce such distortions (adaptation) can provide powerful insights into the computations underlying human visual experience. Previously spatial form and stimulus dynamics were thought to be encoded independently, but here we show that adaptation to stimulus dynamics can sharpen form perception. We find that fast flicker adaptation (FFAd) shifts the tuning of face perception to higher spatial frequencies, enhances the acuity of spatial vision—allowing people to localize inputs with greater precision and to read finer scaled text, and it selectively reduces sensitivity to coarse-scale form signals. These findings are consistent with two interrelated influences: FFAd reduces the responsiveness of magnocellular neurons (which are important for encoding dynamics, but can have poor spatial resolution), and magnocellular responses contribute coarse spatial scale information when the visual system synthesizes form signals. Consequently, when magnocellular responses are mitigated via FFAd, human form perception is transiently sharpened because “blur” signals are mitigated. PMID:27791115

Motivational Differences in Seeking Out Evaluative Categorization Information.

PubMed

Smallman, Rachel; Becker, Brittney

2017-07-01

Previous research shows that people draw finer evaluative distinctions when rating liked versus disliked objects (e.g., wanting a 5-point scale to evaluate liked cuisines and a 3-point scale to rate disliked cuisines). Known as the preference-categorization effect, this pattern may exist not only in how individuals form evaluative distinctions but also in how individuals seek out evaluative information. The current research presents three experiments that examine motivational differences in evaluative information seeking (rating scales and attributes). Experiment 1 found that freedom of choice (the ability to avoid undesirable stimuli) and sensitivity to punishment (as measured by the Behavior Inhibition System/Behavioral Approach System [BIS/BAS] scale) influenced preferences for desirable and undesirable evaluative information in a health-related decision. Experiment 2 examined choice optimization, finding that maximizers prefer finer evaluative information for both liked and disliked options in a consumer task. Experiment 3 found that this pattern generalizes to another type of evaluative categorization, attributes.

Extrusion rate of the Mount St. Helens lava dome estimated from terrestrial imagery, November 2004-December 2005: Chapter 12 in A volcano rekindled: the renewed eruption of Mount St. Helens, 2004-2006

USGS Publications Warehouse

Major, Jon J.; Kingsbury, Cole G.; Poland, Michael P.; LaHusen, Richard G.; Sherrod, David R.; Scott, William E.; Stauffer, Peter H.

2008-01-01

Oblique, terrestrial imagery from a single, fixed-position camera was used to estimate linear extrusion rates during sustained exogenous growth of the Mount St. Helens lava dome from November 2004 through December 2005. During that 14-month period, extrusion rates declined logarithmically from about 8-10 m/d to about 2 m/d. The overall ebbing of effusive output was punctuated, however, by episodes of fluctuating extrusion rates that varied on scales of days to weeks. The overall decline of effusive output and finer scale rate fluctuations correlated approximately with trends in seismicity and deformation. Those correlations portray an extrusion that underwent episodic, broad-scale stick-slip behavior superposed on the finer scale, smaller magnitude stick-slip behavior that has been hypothesized by other researchers to correlate with repetitive, nearly periodic shallow earthquakes.

Parallel Computation of the Regional Ocean Modeling System (ROMS)

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

Wang, P; Song, Y T; Chao, Y

2005-04-05

The Regional Ocean Modeling System (ROMS) is a regional ocean general circulation modeling system solving the free surface, hydrostatic, primitive equations over varying topography. It is free software distributed world-wide for studying both complex coastal ocean problems and the basin-to-global scale ocean circulation. The original ROMS code could only be run on shared-memory systems. With the increasing need to simulate larger model domains with finer resolutions and on a variety of computer platforms, there is a need in the ocean-modeling community to have a ROMS code that can be run on any parallel computer ranging from 10 to hundreds ofmore » processors. Recently, we have explored parallelization for ROMS using the MPI programming model. In this paper, an efficient parallelization strategy for such a large-scale scientific software package, based on an existing shared-memory computing model, is presented. In addition, scientific applications and data-performance issues on a couple of SGI systems, including Columbia, the world's third-fastest supercomputer, are discussed.« less

Using adaptive-mesh refinement in SCFT simulations of surfactant adsorption

NASA Astrophysics Data System (ADS)

Sides, Scott; Kumar, Rajeev; Jamroz, Ben; Crockett, Robert; Pletzer, Alex

2013-03-01

Adsorption of surfactants at interfaces is relevant to many applications such as detergents, adhesives, emulsions and ferrofluids. Atomistic simulations of interface adsorption are challenging due to the difficulty of modeling the wide range of length scales in these problems: the thin interface region in equilibrium with a large bulk region that serves as a reservoir for the adsorbed species. Self-consistent field theory (SCFT) has been extremely useful for studying the morphologies of dense block copolymer melts. Field-theoretic simulations such as these are able to access large length and time scales that are difficult or impossible for particle-based simulations such as molecular dynamics. However, even SCFT methods can be difficult to apply to systems in which small spatial regions might require finer resolution than most of the simulation grid (eg. interface adsorption and confinement). We will present results on interface adsorption simulations using PolySwift++, an object-oriented, polymer SCFT simulation code aided by the Tech-X Chompst library that enables via block-structured AMR calculations with PETSc.

CROSS-SCALE CORRELATIONS AND THE DESIGN AND ANALYSIS OF AVIAN HABITAT SELECTION STUDIES

EPA Science Inventory

It has long been suggested that birds select habitat hierarchically, progressing from coarser to finer spatial scales. This hypothesis, in conjunction with the realization that many organisms likely respond to environmental patterns at multiple spatial scales, has led to a large ...

Structure of the European upper mantle revealed by adjoint tomography

NASA Astrophysics Data System (ADS)

Zhu, Hejun; Bozdağ, Ebru; Peter, Daniel; Tromp, Jeroen

2012-07-01

Images of the European crust and upper mantle, created using seismic tomography, identify the Cenozoic Rift System and related volcanism in central and western Europe. They also reveal subduction and slab roll back in the Mediterranean-Carpathian region. However, existing tomographic models are either high in resolution, but cover only a limited area, or low in resolution, and thus miss the finer-scale details of mantle structure. Here we simultaneously fit frequency-dependent phase anomalies of body and surface waveforms in complete three-component seismograms with an iterative inversion strategy involving adjoint methods, to create a tomographic model of the European upper mantle. We find that many of the smaller-scale structures such as slabs, upwellings and delaminations that emerge naturally in our model are consistent with existing images. However, we also derive some hitherto unidentified structures. Specifically, we interpret fast seismic-wave speeds beneath the Dinarides Mountains, southern Europe, as a signature of northeastward subduction of the Adria plate; slow seismic-wave speeds beneath the northern part of the Rhine Graben as a reservoir connected to the Eifel hotspot; and fast wave-speed anomalies beneath Scandinavia as a lithospheric drip, where the lithosphere is delaminating and breaking away. Our model sheds new light on the enigmatic palaeotectonic history of Europe.

Reconstruction of color images via Haar wavelet based on digital micromirror device

NASA Astrophysics Data System (ADS)

Liu, Xingjiong; He, Weiji; Gu, Guohua

2015-10-01

A digital micro mirror device( DMD) is introduced to form Haar wavelet basis , projecting on the color target image by making use of structured illumination, including red, green and blue light. The light intensity signals reflected from the target image are received synchronously by the bucket detector which has no spatial resolution, converted into voltage signals and then transferred into PC[1] .To reach the aim of synchronization, several synchronization processes are added during data acquisition. In the data collection process, according to the wavelet tree structure, the locations of significant coefficients at the finer scale are predicted by comparing the coefficients sampled at the coarsest scale with the threshold. The monochrome grayscale images are obtained under red , green and blue structured illumination by using Haar wavelet inverse transform algorithm, respectively. The color fusion algorithm is carried on the three monochrome grayscale images to obtain the final color image. According to the imaging principle, the experimental demonstration device is assembled. The letter "K" and the X-rite Color Checker Passport are projected and reconstructed as target images, and the final reconstructed color images have good qualities. This article makes use of the method of Haar wavelet reconstruction, reducing the sampling rate considerably. It provides color information without compromising the resolution of the final image.

Evaluation of near surface ozone and particulate matter in air ...

EPA Pesticide Factsheets

In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher-resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000–2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method’s use for future air quality projections. This paper shows that if emissions inputs and coarse-scale meteorological inputs are reasonably accurate, then air quality can be simulated with acceptable accuracy even wi

High-Resolution Soil Moisture Retrieval using SMAP-L Band Radiometer and RISAT-C band Radar Data for the Indian Subcontinent

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.

Roadmap for Scaling and Multifractals in Geosciences: still a long way to go ?

NASA Astrophysics Data System (ADS)

Schertzer, Daniel; Lovejoy, Shaun

2010-05-01

The interest in scale symmetries (scaling) in Geosciences has never lessened since the first pioneering EGS session on chaos and fractals 22 years ago. The corresponding NP activities have been steadily increasing, covering a wider and wider diversity of geophysical phenomena and range of space-time scales. Whereas interest was initially largely focused on atmospheric turbulence, rain and clouds at small scales, it has quickly broadened to much larger scales and to much wider scale ranges, to include ocean sciences, solid earth and space physics. Indeed, the scale problem being ubiquitous in Geosciences, it is indispensable to share the efforts and the resulting knowledge as much as possible. There have been numerous achievements which have followed from the exploration of larger and larger datasets with finer and finer resolutions, from both modelling and theoretical discussions, particularly on formalisms for intermittency, anisotropy and scale symmetry, multiple scaling (multifractals) vs. simple scaling,. We are now way beyond the early pioneering but tentative attempts using crude estimates of unique scaling exponents to bring some credence to the fact that scale symmetries are key to most nonlinear geoscience problems. Nowadays, we need to better demonstrate that scaling brings effective solutions to geosciences and therefore to society. A large part of the answer corresponds to our capacity to create much more universal and flexible tools to multifractally analyse in straightforward and reliable manners complex and complicated systems such as the climate. Preliminary steps in this direction are already quite encouraging: they show that such approaches explain both the difficulty of classical techniques to find trends in climate scenarios (particularly for extremes) and resolve them with the help of scaling estimators. The question of the reliability and accuracy of these methods is not trivial. After discussing these important, but rather short term issues, we will point out more general questions, which can be put together into the following provocative question: how to convert the classical time evolving deterministic PDE's into dynamical multifractal systems? We will argue that this corresponds to an already active field of research, which include: multifractals as generic solutions of nonlinear PDE (exact results for 1D Burgers equation and a few other caricatures of Navier-Stokes equations, prospects for 3D Burgers equations), cascade structures of numerical weather models, links between multifractal processes and random dynamical systems, and the challenging debate on the most relevant stochastic multifractal formalism, whereas there is already a rather general consent about the deterministic one.

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

DOE PAGES

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

DOE PAGES

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

What spatial scales are believable for climate model projections of sea surface temperature?

NASA Astrophysics Data System (ADS)

Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.

2014-09-01

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.

Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction.

PubMed

Yonehara, Yoshinari; Goto, Yusuke; Yoda, Ken; Watanuki, Yutaka; Young, Lindsay C; Weimerskirch, Henri; Bost, Charles-André; Sato, Katsufumi

2016-08-09

Ocean surface winds are an essential factor in understanding the physical interactions between the atmosphere and the ocean. Surface winds measured by satellite scatterometers and buoys cover most of the global ocean; however, there are still spatial and temporal gaps and finer-scale variations of wind that may be overlooked, particularly in coastal areas. Here, we show that flight paths of soaring seabirds can be used to estimate fine-scale (every 5 min, ∼5 km) ocean surface winds. Fine-scale global positioning system (GPS) positional data revealed that soaring seabirds flew tortuously and ground speed fluctuated presumably due to tail winds and head winds. Taking advantage of the ground speed difference in relation to flight direction, we reliably estimated wind speed and direction experienced by the birds. These bird-based wind velocities were significantly correlated with wind velocities estimated by satellite-borne scatterometers. Furthermore, extensive travel distances and flight duration of the seabirds enabled a wide range of high-resolution wind observations, especially in coastal areas. Our study suggests that seabirds provide a platform from which to measure ocean surface winds, potentially complementing conventional wind measurements by covering spatial and temporal measurement gaps.

Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction

PubMed Central

Yonehara, Yoshinari; Goto, Yusuke; Yoda, Ken; Watanuki, Yutaka; Young, Lindsay C.; Weimerskirch, Henri; Bost, Charles-André; Sato, Katsufumi

2016-01-01

Ocean surface winds are an essential factor in understanding the physical interactions between the atmosphere and the ocean. Surface winds measured by satellite scatterometers and buoys cover most of the global ocean; however, there are still spatial and temporal gaps and finer-scale variations of wind that may be overlooked, particularly in coastal areas. Here, we show that flight paths of soaring seabirds can be used to estimate fine-scale (every 5 min, ∼5 km) ocean surface winds. Fine-scale global positioning system (GPS) positional data revealed that soaring seabirds flew tortuously and ground speed fluctuated presumably due to tail winds and head winds. Taking advantage of the ground speed difference in relation to flight direction, we reliably estimated wind speed and direction experienced by the birds. These bird-based wind velocities were significantly correlated with wind velocities estimated by satellite-borne scatterometers. Furthermore, extensive travel distances and flight duration of the seabirds enabled a wide range of high-resolution wind observations, especially in coastal areas. Our study suggests that seabirds provide a platform from which to measure ocean surface winds, potentially complementing conventional wind measurements by covering spatial and temporal measurement gaps. PMID:27457932

Scaling Optimization of the SIESTA MHD Code

NASA Astrophysics Data System (ADS)

Seal, Sudip; Hirshman, Steven; Perumalla, Kalyan

2013-10-01

SIESTA is a parallel three-dimensional plasma equilibrium code capable of resolving magnetic islands at high spatial resolutions for toroidal plasmas. Originally designed to exploit small-scale parallelism, SIESTA has now been scaled to execute efficiently over several thousands of processors P. This scaling improvement was accomplished with minimal intrusion to the execution flow of the original version. First, the efficiency of the iterative solutions was improved by integrating the parallel tridiagonal block solver code BCYCLIC. Krylov-space generation in GMRES was then accelerated using a customized parallel matrix-vector multiplication algorithm. Novel parallel Hessian generation algorithms were integrated and memory access latencies were dramatically reduced through loop nest optimizations and data layout rearrangement. These optimizations sped up equilibria calculations by factors of 30-50. It is possible to compute solutions with granularity N/P near unity on extremely fine radial meshes (N > 1024 points). Grid separation in SIESTA, which manifests itself primarily in the resonant components of the pressure far from rational surfaces, is strongly suppressed by finer meshes. Large problem sizes of up to 300 K simultaneous non-linear coupled equations have been solved on the NERSC supercomputers. Work supported by U.S. DOE under Contract DE-AC05-00OR22725 with UT-Battelle, LLC.

Spatial consistency of Chinook salmon redd distribution within and among years in the Cowlitz River, Washington

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

Klett, Katherine J.; Torgersen, Christian; Henning, Julie

2013-04-28

We investigated the spawning patterns of Chinook salmon Oncorhynchus tshawytscha on the lower Cowlitz River, Washington (USA) using a unique set of fine- and coarse-scale 35 temporal and spatial data collected during bi-weekly 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 global positioning system (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 yearmore » with little variation among years. On a coarse scale, five years (1993, 1998, 2000, 2002, and 2009) were compared for reoccupation. Redd locations were highly correlated among years resulting in a minimum correlation coefficient of 0.90 (adjusted P = 0.002). Comparisons on a fine scale (500 m) between 2008 and 2009 also revealed a high degree of consistency among redd locations (P < 0.001). On a finer temporal scale, we observed that salmon spawned in the same sections during the first and last week (2008: P < 0.02; and 2009: P < 0.001). Redds were clustered in both 2008 and 2009 (P < 0.001). 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.« less

Predicted deep-sea coral habitat suitability for the U.S. West coast.

PubMed

Guinotte, John M; Davies, Andrew J

2014-01-01

Regional scale habitat suitability models provide finer scale resolution and more focused predictions of where organisms may occur. Previous modelling approaches have focused primarily on local and/or global scales, while regional scale models have been relatively few. In this study, regional scale predictive habitat models are presented for deep-sea corals for the U.S. West Coast (California, Oregon and Washington). Model results are intended to aid in future research or mapping efforts and to assess potential coral habitat suitability both within and outside existing bottom trawl closures (i.e. Essential Fish Habitat (EFH)) and identify suitable habitat within U.S. National Marine Sanctuaries (NMS). Deep-sea coral habitat suitability was modelled at 500 m×500 m spatial resolution using a range of physical, chemical and environmental variables known or thought to influence the distribution of deep-sea corals. Using a spatial partitioning cross-validation approach, maximum entropy models identified slope, temperature, salinity and depth as important predictors for most deep-sea coral taxa. Large areas of highly suitable deep-sea coral habitat were predicted both within and outside of existing bottom trawl closures and NMS boundaries. Predicted habitat suitability over regional scales are not currently able to identify coral areas with pin point accuracy and probably overpredict actual coral distribution due to model limitations and unincorporated variables (i.e. data on distribution of hard substrate) that are known to limit their distribution. Predicted habitat results should be used in conjunction with multibeam bathymetry, geological mapping and other tools to guide future research efforts to areas with the highest probability of harboring deep-sea corals. Field validation of predicted habitat is needed to quantify model accuracy, particularly in areas that have not been sampled.

Predicted Deep-Sea Coral Habitat Suitability for the U.S. West Coast

PubMed Central

Guinotte, John M.; Davies, Andrew J.

2014-01-01

Regional scale habitat suitability models provide finer scale resolution and more focused predictions of where organisms may occur. Previous modelling approaches have focused primarily on local and/or global scales, while regional scale models have been relatively few. In this study, regional scale predictive habitat models are presented for deep-sea corals for the U.S. West Coast (California, Oregon and Washington). Model results are intended to aid in future research or mapping efforts and to assess potential coral habitat suitability both within and outside existing bottom trawl closures (i.e. Essential Fish Habitat (EFH)) and identify suitable habitat within U.S. National Marine Sanctuaries (NMS). Deep-sea coral habitat suitability was modelled at 500 m×500 m spatial resolution using a range of physical, chemical and environmental variables known or thought to influence the distribution of deep-sea corals. Using a spatial partitioning cross-validation approach, maximum entropy models identified slope, temperature, salinity and depth as important predictors for most deep-sea coral taxa. Large areas of highly suitable deep-sea coral habitat were predicted both within and outside of existing bottom trawl closures and NMS boundaries. Predicted habitat suitability over regional scales are not currently able to identify coral areas with pin point accuracy and probably overpredict actual coral distribution due to model limitations and unincorporated variables (i.e. data on distribution of hard substrate) that are known to limit their distribution. Predicted habitat results should be used in conjunction with multibeam bathymetry, geological mapping and other tools to guide future research efforts to areas with the highest probability of harboring deep-sea corals. Field validation of predicted habitat is needed to quantify model accuracy, particularly in areas that have not been sampled. PMID:24759613

Fine Particulate Matter and Cardiovascular Disease: Comparison of Assessment Methods for Long-term Exposure

EPA Science Inventory

Background Adverse cardiovascular events have been linked with PM2.5 exposure obtained primarily from air quality monitors, which rarely co-locate with participant residences. Modeled PM2.5 predictions at finer resolution may more accurately predict residential exposure; however...

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

Combining satellite photographs and raster lidar data for channel connectivity in tidal marshes.

NASA Astrophysics Data System (ADS)

Li, Zhi; Hodges, Ben

2017-04-01

High resolution airborne lidar is capable of providing topographic detail down to the 1 x 1 m scale or finer over large tidal marshes of a river delta. Such data sets can be challenging to develop and ground-truth due to the inherent complexities of the environment, the relatively small changes in elevation throughout a marsh, and practical difficulties in accessing the variety of flooded, dry, and muddy regions. Standard lidar point-cloud processing techniques (as typically applied in large lidar data collection program) have a tendency to mis-identify narrow channels and water connectivity in a marsh, which makes it difficult to directly use such data for modeling marsh flows. Unfortunately, it is not always practical, or even possible, to access the point cloud and re-analyze the raw lidar data when discrepancies have been found in a raster work product. Faced with this problem in preparing a model of the Trinity River delta (Texas, USA), we developed an approach to integrating analysis of a lidar-based raster with satellite images. Our primary goal was to identify the clear land/water boundaries needed to identify channelization in the available rasterized lidar data. The channel extraction method uses pixelized satellite photographs that are stretched/distorted with image-processing techniques to match identifiable control features in both lidar and photographic data sets. A kmeans clustering algorithm was applied cluster pixels based on their colors, which is effective in separating land and water in a satellite photograph. The clustered image was matched to the lidar data such that the combination shows the channel network. In effect, we are able to use the fact that the satellite photograph is higher resolution than the lidar data, and thus provides connectivity in the clustering at a finer scale. The principal limitation of the method is the where the satellite image and lidar suffer from similar problems For example, vegetation overhanging a narrow channel might show up as higher-elevation land in the lidar data an also as a non-water cluster color in the satellite photo.

Los Angeles and San Diego Margin High-Resolution Multibeam Bathymetry and Backscatter Data

USGS Publications Warehouse

Dartnell, Peter; Gardner, James V.; Mayer, Larry A.; Hughes-Clarke, John E.

2004-01-01

Summary -- The U.S. Geological Survey in cooperation with the University of New Hampshire and the University of New Brunswick mapped the nearshore regions off Los Angeles and San Diego, California using multibeam echosounders. Multibeam bathymetry and co-registered, corrected acoustic backscatter were collected in water depths ranging from about 3 to 900 m offshore Los Angeles and in water depths ranging from about 17 to 1230 m offshore San Diego. Continuous, 16-m spatial resolution, GIS ready format data of the entire Los Angeles Margin and San Diego Margin are available online as separate USGS Open-File Reports. For ongoing research, the USGS has processed sub-regions within these datasets at finer resolutions. The resolution of each sub-region was determined by the density of soundings within the region. This Open-File Report contains the finer resolution multibeam bathymetry and acoustic backscatter data that the USGS, Western Region, Coastal and Marine Geology Team has processed into GIS ready formats as of April 2004. The data are available in ArcInfo GRID and XYZ formats. See the Los Angeles or San Diego maps for the sub-region locations. These datasets in their present form were not originally intended for publication. The bathymetry and backscatter have data-collection and processing artifacts. These data are being made public to fulfill a Freedom of Information Act request. Care must be taken not to confuse artifacts with real seafloor morphology and acoustic backscatter.

Efficient non-hydrostatic modelling of 3D wave-induced currents using a subgrid approach

NASA Astrophysics Data System (ADS)

Rijnsdorp, Dirk P.; Smit, Pieter B.; Zijlema, Marcel; Reniers, Ad J. H. M.

2017-08-01

Wave-induced currents are an ubiquitous feature in coastal waters that can spread material over the surf zone and the inner shelf. These currents are typically under resolved in non-hydrostatic wave-flow models due to computational constraints. Specifically, the low vertical resolutions adequate to describe the wave dynamics - and required to feasibly compute at the scales of a field site - are too coarse to account for the relevant details of the three-dimensional (3D) flow field. To describe the relevant dynamics of both wave and currents, while retaining a model framework that can be applied at field scales, we propose a two grid approach to solve the governing equations. With this approach, the vertical accelerations and non-hydrostatic pressures are resolved on a relatively coarse vertical grid (which is sufficient to accurately resolve the wave dynamics), whereas the horizontal velocities and turbulent stresses are resolved on a much finer subgrid (of which the resolution is dictated by the vertical scale of the mean flows). This approach ensures that the discrete pressure Poisson equation - the solution of which dominates the computational effort - is evaluated on the coarse grid scale, thereby greatly improving efficiency, while providing a fine vertical resolution to resolve the vertical variation of the mean flow. This work presents the general methodology, and discusses the numerical implementation in the SWASH wave-flow model. Model predictions are compared with observations of three flume experiments to demonstrate that the subgrid approach captures both the nearshore evolution of the waves, and the wave-induced flows like the undertow profile and longshore current. The accuracy of the subgrid predictions is comparable to fully resolved 3D simulations - but at much reduced computational costs. The findings of this work thereby demonstrate that the subgrid approach has the potential to make 3D non-hydrostatic simulations feasible at the scale of a realistic coastal region.

LES-based filter-matrix lattice Boltzmann model for simulating fully developed turbulent channel flow

NASA Astrophysics Data System (ADS)

Zhuo, Congshan; Zhong, Chengwen

2016-11-01

In this paper, a three-dimensional filter-matrix lattice Boltzmann (FMLB) model based on large eddy simulation (LES) was verified for simulating wall-bounded turbulent flows. The Vreman subgrid-scale model was employed in the present FMLB-LES framework, which had been proved to be capable of predicting turbulent near-wall region accurately. The fully developed turbulent channel flows were performed at a friction Reynolds number Reτ of 180. The turbulence statistics computed from the present FMLB-LES simulations, including mean stream velocity profile, Reynolds stress profile and root-mean-square velocity fluctuations greed well with the LES results of multiple-relaxation-time (MRT) LB model, and some discrepancies in comparison with those direct numerical simulation (DNS) data of Kim et al. was also observed due to the relatively low grid resolution. Moreover, to investigate the influence of grid resolution on the present LES simulation, a DNS simulation on a finer gird was also implemented by present FMLB-D3Q19 model. Comparisons of detailed computed various turbulence statistics with available benchmark data of DNS showed quite well agreement.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling.

PubMed

Stoy, Paul C; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

Design of a 9K illumina BeadChip for polar bears (Ursus maritimus) from RAD and transcriptome sequencing.

PubMed

Malenfant, René M; Coltman, David W; Davis, Corey S

2015-05-01

Single-nucleotide polymorphisms (SNPs) offer numerous advantages over anonymous markers such as microsatellites, including improved estimation of population parameters, finer-scale resolution of population structure and more precise genomic dissection of quantitative traits. However, many SNPs are needed to equal the resolution of a single microsatellite, and reliable large-scale genotyping of SNPs remains a challenge in nonmodel species. Here, we document the creation of a 9K Illumina Infinium BeadChip for polar bears (Ursus maritimus), which will be used to investigate: (i) the fine-scale population structure among Canadian polar bears and (ii) the genomic architecture of phenotypic traits in the Western Hudson Bay subpopulation. To this end, we used restriction-site associated DNA (RAD) sequencing from 38 bears across their circumpolar range, as well as blood/fat transcriptome sequencing of 10 individuals from Western Hudson Bay. Six-thousand RAD SNPs and 3000 transcriptomic SNPs were selected for the chip, based primarily on genomic spacing and gene function respectively. Of the 9000 SNPs ordered from Illumina, 8042 were successfully printed, and - after genotyping 1450 polar bears - 5441 of these SNPs were found to be well clustered and polymorphic. Using this array, we show rapid linkage disequilibrium decay among polar bears, we demonstrate that in a subsample of 78 individuals, our SNPs detect known genetic structure more clearly than 24 microsatellites genotyped for the same individuals and that these results are not driven by the SNP ascertainment scheme. Here, we present one of the first large-scale genotyping resources designed for a threatened species. © 2014 John Wiley & Sons Ltd.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling

PubMed Central

Stoy, Paul C.; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes. PMID:26067835

Understanding the climate-included variations in the seasonal water demands of irrigated crops in Northern India

NASA Astrophysics Data System (ADS)

Bhattarai, N.; Jain, M.

2016-12-01

Expected changes in temperature and precipitation patterns in the rice-wheat belt of Northern India have implications for balancing crop water demand and available water resources. Because the impacts of water scarcity and reduced crop production are realized at a local scale, water-saving interventions are most effective when implemented locally. However, a paucity of fine-scale studies on the relationship between variations in climate and crop water demand has limited our ability to effectively implement such interventions. In an effort to better understand the responses of irrigated crops to changing climate in Northern India at finer-scales, we propose a remote sensing based semi-empirical approach. First, we employ a multi-model surface energy balance (SEB) approach to map seasonal evapotranspiration (ET)/water use (1995-2015) at 30 to 100 m resolution from space and investigate how seasonal and inter-annual variations in temperature and precipitation are associated with regional surface-energy budgets. Second, using remote estimates of ET and other biophysical variables, such as vegetation indices, land surface temperature, and albedo, we will explain the possible relationships between climate change and seasonal water demands of crops. Our estimates of high/moderate resolution (30 to 100 m) seasonal ET maps can make clear distinctions between impacts of climate variations on crop water demand at field, plot, and regional scales in Northern India. Finally, by improving our ability to identify targeted area for water-saving interventions, this study supports agricultural resiliency of Northern India in the face of climate change.

Unresolved fine-scale structure in solar coronal loop-tops

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

Scullion, E.; Van der Voort, L. Rouppe; Wedemeyer, S.

2014-12-10

New and advanced space-based observing facilities continue to lower the resolution limit and detect solar coronal loops in greater detail. We continue to discover even finer substructures within coronal loop cross-sections, in order to understand the nature of the solar corona. Here, we push this lower limit further to search for the finest coronal loop substructures, through taking advantage of the resolving power of the Swedish 1 m Solar Telescope/CRisp Imaging Spectro-Polarimeter (CRISP), together with co-observations from the Solar Dynamics Observatory/Atmospheric Image Assembly (AIA). High-resolution imaging of the chromospheric Hα 656.28 nm spectral line core and wings can, under certainmore » circumstances, allow one to deduce the topology of the local magnetic environment of the solar atmosphere where its observed. Here, we study post-flare coronal loops, which become filled with evaporated chromosphere that rapidly condenses into chromospheric clumps of plasma (detectable in Hα) known as a coronal rain, to investigate their fine-scale structure. We identify, through analysis of three data sets, large-scale catastrophic cooling in coronal loop-tops and the existence of multi-thermal, multi-stranded substructures. Many cool strands even extend fully intact from loop-top to footpoint. We discover that coronal loop fine-scale strands can appear bunched with as many as eight parallel strands within an AIA coronal loop cross-section. The strand number density versus cross-sectional width distribution, as detected by CRISP within AIA-defined coronal loops, most likely peaks at well below 100 km, and currently, 69% of the substructure strands are statistically unresolved in AIA coronal loops.« less

Challenges of model transferability to data-scarce regions (Invited)

NASA Astrophysics Data System (ADS)

Samaniego, L. E.

2013-12-01

Developing the ability to globally predict the movement of water on the land surface at spatial scales from 1 to 5 km constitute one of grand challenges in land surface modelling. Copying with this grand challenge implies that land surface models (LSM) should be able to make reliable predictions across locations and/or scales other than those used for parameter estimation. In addition to that, data scarcity and quality impose further difficulties in attaining reliable predictions of water and energy fluxes at the scales of interest. Current computational limitations impose also seriously limitations to exhaustively investigate the parameter space of LSM over large domains (e.g. greater than half a million square kilometers). Addressing these challenges require holistic approaches that integrate the best techniques available for parameter estimation, field measurements and remotely sensed data at their native resolutions. An attempt to systematically address these issues is the multiscale parameterisation technique (MPR) that links high resolution land surface characteristics with effective model parameters. This technique requires a number of pedo-transfer functions and a much fewer global parameters (i.e. coefficients) to be inferred by calibration in gauged basins. The key advantage of this technique is the quasi-scale independence of the global parameters which enables to estimate global parameters at coarser spatial resolutions and then to transfer them to (ungauged) areas and scales of interest. In this study we show the ability of this technique to reproduce the observed water fluxes and states over a wide range of climate and land surface conditions ranging from humid to semiarid and from sparse to dense forested regions. Results of transferability of global model parameters in space (from humid to semi-arid basins) and across scales (from coarser to finer) clearly indicate the robustness of this technique. Simulations with coarse data sets (e.g. EOBS forcing 25x25 km2, FAO soil map 1:5000000) using parameters obtained with high resolution information (REGNIE forcing 1x1 km2, BUEK soil map 1:1000000) in different climatic regions indicate the potential of MPR for prediction in data-scarce regions. In this presentation, we will also discuss how the transferability of global model parameters across scales and locations helps to identify deficiencies in model structure and regionalization functions.

In need of combined topography and bathymetry DEM

NASA Astrophysics Data System (ADS)

Kisimoto, K.; Hilde, T.

2003-04-01

In many geoscience applications, digital elevation models (DEMs) are now more commonly used at different scales and greater resolution due to the great advancement in computer technology. Increasing the accuracy/resolution of the model and the coverage of the terrain (global model) has been the goal of users as mapping technology has improved and computers get faster and cheaper. The ETOPO5 (5 arc minutes spatial resolution land and seafloor model), initially developed in 1988 by Margo Edwards, then at Washington University, St. Louis, MO, has been the only global terrain model for a long time, and it is now being replaced by three new topographic and bathymetric DEMs, i.e.; the ETOPO2 (2 arc minutes spatial resolution land and seafloor model), the GTOPO30 land model with a spatial resolution of 30 arc seconds (c.a. 1km at equator) and the 'GEBCO 1-MINUTE GLOBAL BATHYMETRIC GRID' ocean floor model with a spatial resolution of 1 arc minute (c.a. 2 km at equator). These DEMs are products of projects through which compilation and reprocessing of existing and/or new datasets were made to meet user's new requirements. These ongoing efforts are valuable and support should be continued to refine and update these DEMs. On the other hand, a different approach to create a global bathymetric (seafloor) database exists. A method to estimate the seafloor topography from satellite altimetry combined with existing ships' conventional sounding data was devised and a beautiful global seafloor database created and made public by W.H. Smith and D.T. Sandwell in 1997. The big advantage of this database is the uniformity of coverage, i.e. there is no large area where depths are missing. It has a spatial resolution of 2 arc minute. Another important effort is found in making regional, not global, seafloor databases with much finer resolutions in many countries. The Japan Hydrographic Department has compiled and released a 500m-grid topography database around Japan, J-EGG500, in 1999. Although the coverage of this database is only a small portion of the Earth, the database has been highly appreciated in the academic community, and accepted in surprise by the general public when the database was displayed in 3D imagery to show its quality. This database could be rather smoothly combined with the finer land DEM of 250m spatial resolution (Japan250m.grd, K. Kisimoto, 2000). One of the most important applications of this combined DEM of topography and bathymetry is tsunami modeling. Understanding of the coastal environment, management and development of the coastal region are other fields in need of these data. There is, however, an important issue to consider when we create a combined DEM of topography and bathymetry in finer resolutions. The problem arises from the discrepancy of the standard datum planes or reference levels used for topographic leveling and bathymetric sounding. Land topography (altitude) is defined by leveling from the single reference point determined by average mean sea level, in other words, land height is measured from the geoid. On the other hand, depth charts are made based on depth measured from locally determined reference sea surface level, and this value of sea surface level is taken from the long term average of the lowest tidal height. So, to create a combined DEM of topography and bathymetry in very fine scale, we need to avoid this inconsistency between height and depth across the coastal region. Height and depth should be physically continuous relative to a single reference datum across the coast within such new high resolution DEMs. (N.B. Coast line is not equal to 'altitude-zero line' nor 'depth-zero line'. It is defined locally as the long term average of the highest tide level.) All of this said, we still need a lot of work on the ocean side. Global coverage with detailed bathymetric mapping is still poor. Seafloor imaging and other geophysical measurements/experiments should be organized and conducted internationally and interdisciplinary ways more than ever. We always need greater technological advancement and application of this technology in marine sciences, and more enthusiastic minds of seagoing researchers as well. Recent seafloor mapping technology/quality both in bathymetry and imagery is very promising and even favorably compared with the terrain mapping. We discuss and present on recent achievement and needs on the seafloor mapping using several most up-to-date global- and regional- DEMs available for science community at the poster session.

Surface geophysical methods for characterising frozen ground in transitional permafrost landscapes

USGS Publications Warehouse

Briggs, Martin A.; Campbell, Seth; Nolan, Jay; Walvoord, Michelle Ann; Ntarlagiannis, Dimitrios; Day-Lewis, Frederick D.; Lane, John W.

2017-01-01

The distribution of shallow frozen ground is paramount to research in cold regions, and is subject to temporal and spatial changes influenced by climate, landscape disturbance and ecosystem succession. Remote sensing from airborne and satellite platforms is increasing our understanding of landscape-scale permafrost distribution, but typically lacks the resolution to characterise finer-scale processes and phenomena, which are better captured by integrated surface geophysical methods. Here, we demonstrate the use of electrical resistivity imaging (ERI), electromagnetic induction (EMI), ground penetrating radar (GPR) and infrared imaging over multiple summer field seasons around the highly dynamic Twelvemile Lake, Yukon Flats, central Alaska, USA. Twelvemile Lake has generally receded in the past 30 yr, allowing permafrost aggradation in the receded margins, resulting in a mosaic of transient frozen ground adjacent to thick, older permafrost outside the original lakebed. ERI and EMI best evaluated the thickness of shallow, thin permafrost aggradation, which was not clear from frost probing or GPR surveys. GPR most precisely estimated the depth of the active layer, which forward electrical resistivity modelling indicated to be a difficult target for electrical methods, but could be more tractable in time-lapse mode. Infrared imaging of freshly dug soil pit walls captured active-layer thermal gradients at unprecedented resolution, which may be useful in calibrating emerging numerical models. GPR and EMI were able to cover landscape scales (several kilometres) efficiently, and new analysis software showcased here yields calibrated EMI data that reveal the complicated distribution of shallow permafrost in a transitional landscape.

Thoughts on Scale

ERIC Educational Resources Information Center

Schoenfeld, Alan H.

2015-01-01

This essay reflects on the challenges of thinking about scale--of making sense of phenomena such as continuous professional development (CPD) at the system level, while holding on to detail at the finer grain size(s) of implementation. The stimuli for my reflections are three diverse studies of attempts at scale--an attempt to use ideas related to…

Using an Ecological Land Hierarchy to Predict Seasonal-Wetland Abundance in Upland Forests

Treesearch

Brian J. Palik; Richard Buech; Leanne Egeland

2003-01-01

Hierarchy theory, when applied to landscapes, predicts that broader-scale ecosystems constrain the development of finer-scale, nested ecosystems. This prediction finds application in hierarchical land classifications. Such classifications typically apply to physiognomically similar ecosystems, or ecological land units, e.g., a set of multi-scale forest ecosystems. We...

Impact of high-resolution a priori profiles on satellite-based formaldehyde retrievals

NASA Astrophysics Data System (ADS)

Kim, Si-Wan; Natraj, Vijay; Lee, Seoyoung; Kwon, Hyeong-Ahn; Park, Rokjin; de Gouw, Joost; Frost, Gregory; Kim, Jhoon; Stutz, Jochen; Trainer, Michael; Tsai, Catalina; Warneke, Carsten

2018-06-01

Formaldehyde (HCHO) is either directly emitted from sources or produced during the oxidation of volatile organic compounds (VOCs) in the troposphere. It is possible to infer atmospheric HCHO concentrations using space-based observations, which may be useful for studying emissions and tropospheric chemistry at urban to global scales depending on the quality of the retrievals. In the near future, an unprecedented volume of satellite-based HCHO measurement data will be available from both geostationary and polar-orbiting platforms. Therefore, it is essential to develop retrieval methods appropriate for the next-generation satellites that measure at higher spatial and temporal resolution than the current ones. In this study, we examine the importance of fine spatial and temporal resolution a priori profile information on the retrieval by conducting approximately 45 000 radiative transfer (RT) model calculations in the Los Angeles Basin (LA Basin) megacity. Our analyses suggest that an air mass factor (AMF, a factor converting observed slant columns to vertical columns) based on fine spatial and temporal resolution a priori profiles can better capture the spatial distributions of the enhanced HCHO plumes in an urban area than the nearly constant AMFs used for current operational products by increasing the columns by ˜ 50 % in the domain average and up to 100 % at a finer scale. For this urban area, the AMF values are inversely proportional to the magnitude of the HCHO mixing ratios in the boundary layer. Using our optimized model HCHO results in the Los Angeles Basin that mimic the HCHO retrievals from future geostationary satellites, we illustrate the effectiveness of HCHO data from geostationary measurements for understanding and predicting tropospheric ozone and its precursors.

Development and application of a large scale river system model for National Water Accounting in Australia

NASA Astrophysics Data System (ADS)

Dutta, Dushmanta; Vaze, Jai; Kim, Shaun; Hughes, Justin; Yang, Ang; Teng, Jin; Lerat, Julien

2017-04-01

Existing global and continental scale river models, mainly designed for integrating with global climate models, are of very coarse spatial resolutions and lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing water accounts, which have become increasingly important for water resources planning and management at regional and national scales. A continental scale river system model called Australian Water Resource Assessment River System model (AWRA-R) has been developed and implemented for national water accounting in Australia using a node-link architecture. The model includes major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. Two key components of the model are an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. The results in the Murray-Darling Basin shows highly satisfactory performance of the model with median daily Nash-Sutcliffe Efficiency (NSE) of 0.64 and median annual bias of less than 1% for the period of calibration (1970-1991) and median daily NSE of 0.69 and median annual bias of 12% for validation period (1992-2014). The results have demonstrated that the performance of the model is less satisfactory when the key processes such as overbank flow, groundwater seepage and irrigation diversion are switched off. The AWRA-R model, which has been operationalised by the Australian Bureau of Meteorology for continental scale water accounting, has contributed to improvements in the national water account by substantially reducing accounted different volume (gain/loss).

Verification of Global Assimilation of Ionospheric Measurements Gauss Markov (GAIM-GM) Model Forecast Accuracy

DTIC Science & Technology

2011-09-01

m b e r o f O cc u rr e n ce s 50 ( a ) Kp 0-3 (b) Kp 4-9 Figure 25. Scatter plot of...dependent physics based model that uses the Ionospheric Forecast Model ( IFM ) as a background model upon which perturbations are imposed via a Kalman filter...vertical output resolution as the IFM . GAIM-GM can also be run in a regional mode with a finer resolution (Scherliess et al., 2006). GAIM-GM is

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Bhaskar, A.; Fleming, B.; Hogan, D. M.

2016-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Burke, W.; Tague, C.

2017-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Integrating Landsat Data and High-Resolution Imagery for Applied Conservation Assessment of Forest Cover in Latin American Heterogenous Landscapes

NASA Astrophysics Data System (ADS)

Thomas, N.; Rueda, X.; Lambin, E.; Mendenhall, C. D.

2012-12-01

Large intact forested regions of the world are known to be critical to maintaining Earth's climate, ecosystem health, and human livelihoods. Remote sensing has been successfully implemented as a tool to monitor forest cover and landscape dynamics over broad regions. Much of this work has been done using coarse resolution sensors such as AVHRR and MODIS in combination with moderate resolution sensors, particularly Landsat. Finer scale analysis of heterogeneous and fragmented landscapes is commonly performed with medium resolution data and has had varying success depending on many factors including the level of fragmentation, variability of land cover types, patch size, and image availability. Fine scale tree cover in mixed agricultural areas can have a major impact on biodiversity and ecosystem sustainability but may often be inadequately captured with the global to regional (coarse resolution and moderate resolution) satellite sensors and processing techniques widely used to detect land use and land cover changes. This study investigates whether advanced remote sensing methods are able to assess and monitor percent tree canopy cover in spatially complex human-dominated agricultural landscapes that prove challenging for traditional mapping techniques. Our study areas are in high altitude, mixed agricultural coffee-growing regions in Costa Rica and the Colombian Andes. We applied Random Forests regression tree analysis to Landsat data along with additional spectral, environmental, and spatial variables to predict percent tree canopy cover at 30m resolution. Image object-based texture, shape, and neighborhood metrics were generated at the Landsat scale using eCognition and included in the variable suite. Training and validation data was generated using high resolution imagery from digital aerial photography at 1m to 2.5 m resolution. Our results are promising with Pearson's correlation coefficients between observed and predicted percent tree canopy cover of .86 (Costa Rica) and .83 (Colombia). The tree cover mapping developed here supports two distinct projects on sustaining biodiversity and natural and human capital: in Costa Rica the tree canopy cover map is utilized to predict bird community composition; and in Colombia the mapping is performed for two time periods and used to assess the impact of coffee eco-certification programs on the landscape. This research identifies ways to leverage readily available, high quality, and cost-free Landsat data or other medium resolution satellite data sources in combination with high resolution data, such as that frequently available through Google Earth, to monitor and support sustainability efforts in fragmented and heterogeneous landscapes.

The 1 km resolution global data set: needs of the International Geosphere Biosphere Programme

USGS Publications Warehouse

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.

Spatial Variability of Wet Troposphere Delays Over Inland Water Bodies

NASA Astrophysics Data System (ADS)

Mehran, Ali; Clark, Elizabeth A.; Lettenmaier, Dennis P.

2017-11-01

Satellite radar altimetry has enabled the study of water levels in large lakes and reservoirs at a global scale. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission (scheduled launch 2020) will simultaneously measure water surface extent and elevation at an unprecedented accuracy and resolution. However, SWOT retrieval accuracy will be affected by a number of factors, including wet tropospheric delay—the delay in the signal's passage through the atmosphere due to atmospheric water content. In past applications, the wet tropospheric delay over large inland water bodies has been corrected using atmospheric moisture profiles based on atmospheric reanalysis data at relatively coarse (tens to hundreds of kilometers) spatial resolution. These products cannot resolve subgrid variations in wet tropospheric delays at the spatial resolutions (of 1 km and finer) that SWOT is intended to resolve. We calculate zenith wet tropospheric delays (ZWDs) and their spatial variability from Weather Research and Forecasting (WRF) numerical weather prediction model simulations at 2.33 km spatial resolution over the southwestern U.S., with attention in particular to Sam Rayburn, Ray Hubbard, and Elephant Butte Reservoirs which have width and length dimensions that are of order or larger than the WRF spatial resolution. We find that spatiotemporal variability of ZWD over the inland reservoirs depends on climatic conditions at the reservoir location, as well as distance from ocean, elevation, and surface area of the reservoir, but that the magnitude of subgrid variability (relative to analysis and reanalysis products) is generally less than 10 mm.

Large-Eddy Simulation Comparison of Neutral Flow Over a Canopy: Sensitivities to Physical and Numerical Conditions, and Similarity to Other Representations

NASA Astrophysics Data System (ADS)

Ouwersloot, H. G.; Moene, A. F.; Attema, J. J.; de Arellano, J. Vilà-Guerau

2017-01-01

The representation of a neutral atmospheric flow over roughness elements simulating a vegetation canopy is compared between two large-eddy simulation models, wind-tunnel data and recently updated empirical flux-gradient relationships. Special attention is devoted to the dynamics in the roughness sublayer above the canopy layer, where turbulence is most intense. By demonstrating that the flow properties are consistent across these different approaches, confidence in the individual independent representations is bolstered. Systematic sensitivity analyses with the Dutch Atmospheric Large-Eddy Simulation model show that the transition in the one-sided plant-area density from the canopy layer to unobstructed air potentially alters the flow in the canopy and roughness sublayer. Anomalously induced fluctuations can be fully suppressed by spreading the transition over four steps. Finer vertical resolutions only serve to reduce the magnitude of these fluctuations, but do not prevent them. To capture the general dynamics of the flow, a resolution of 10 % of the canopy height is found to suffice, while a finer resolution still improves the representation of the turbulent kinetic energy. Finally, quadrant analyses indicate that momentum transport is dominated by the mean velocity components within each quadrant. Consequently, a mass-flux approach can be applied to represent the momentum flux.

Multi-resolution MPS method

NASA Astrophysics Data System (ADS)

Tanaka, Masayuki; Cardoso, Rui; Bahai, Hamid

2018-04-01

In this work, the Moving Particle Semi-implicit (MPS) method is enhanced for multi-resolution problems with different resolutions at different parts of the domain utilising a particle splitting algorithm for the finer resolution and a particle merging algorithm for the coarser resolution. The Least Square MPS (LSMPS) method is used for higher stability and accuracy. Novel boundary conditions are developed for the treatment of wall and pressure boundaries for the Multi-Resolution LSMPS method. A wall is represented by polygons for effective simulations of fluid flows with complex wall geometries and the pressure boundary condition allows arbitrary inflow and outflow, making the method easier to be used in flow simulations of channel flows. By conducting simulations of channel flows and free surface flows, the accuracy of the proposed method was verified.

Assessing the competing roles of model resolution and meteorological forcing fidelity in hyperresolution simulations of snowpack and streamflow in the southern Rocky Mountains

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Dugger, A. L.; Karsten, L. R.; Barlage, M. J.; Sampson, K. M.; Yu, W.; Pan, L.; McCreight, J. L.; Howard, K.; Busto, J.; Deems, J. S.

2017-12-01

Hydrometeorological processes vary over comparatively short length scales in regions of complex terrain such as the southern Rocky Mountains. Changes in temperature, precipitation, wind and solar radiation can vary significantly across elevation gradients, terrain landform and land cover conditions throughout the region. Capturing such variability in hydrologic models can necessitate the utilization of so-called `hyper-resolution' spatial meshes with effective element spacings of less than 100m. However, it is often difficult to obtain meteorological forcings of high quality in such regions at those resolutions which can result in significant uncertainty in fundamental in hydrologic model inputs. In this study we examine the comparative influences of meteorological forcing data fidelity and spatial resolution on seasonal simulations of snowpack evolution, runoff and streamflow in a set of high mountain watersheds in southern Colorado. We utilize the operational, NOAA National Water Model configuration of the community WRF-Hydro system as a baseline and compare against it, additional model scenarios with differing specifications of meteorological forcing data, with and without topographic downscaling adjustments applied, with and without experimental high resolution radar derived precipitation estimates and with WRF-Hydro configurations of progressively finer spatial resolution. The results suggest significant influence from and importance of meteorological downscaling techniques in controlling spatial distributions of meltout and runoff timing. The use of radar derived precipitation exhibits clear sensitivity on hydrologic simulation skill compared with the use of coarser resolution, background precipitation analyses. Advantages and disadvantages of the utilization of progressively higher resolution model configurations both in terms of computational requirements and model fidelity are also discussed.

Evaluating community–environment relationships along fine to broad taxonomic resolutions reveals evolutionary forces underlying community assembly

PubMed Central

Lu, Hsiao-Pei; Yeh, Yi-Chun; Sastri, Akash R; Shiah, Fuh-Kwo; Gong, Gwo-Ching; Hsieh, Chih-hao

2016-01-01

We propose a method for detecting evolutionary forces underlying community assembly by quantifying the strength of community–environment relationships hierarchically along taxonomic ranks. This approach explores the potential role of phylogenetic conservatism on habitat preferences: wherein, phylogenetically related taxa are expected to exhibit similar environmental responses. Thus, when niches are conserved, broader taxonomic classification should not diminish the strength of community–environment relationships and may even yield stronger associations by summarizing occurrences and abundances of ecologically equivalent finely resolved taxa. In contrast, broader taxonomic classification should weaken community–environment relationships when niches are under great divergence (that is, by combining finer taxa with distinct environmental responses). Here, we quantified the strength of community–environment relationships using distance-based redundancy analysis, focusing on soil and seawater prokaryotic communities. We considered eight case studies (covering a variety of sampling scales and sequencing strategies) and found that the variation in community composition explained by environmental factors either increased or remained constant with broadening taxonomic resolution from species to order or even phylum level. These results support the niche conservatism hypothesis and indicate that broadening taxonomic resolution may strengthen niche-related signals by removing uncertainty in quantifying spatiotemporal distributions of finely resolved taxa, reinforcing the current notion of ecological coherence in deep prokaryotic branches. PMID:27177191

Process-based model predictions of hurricane induced morphodynamic change on low-lying barrier islands

USGS Publications Warehouse

Plant, Nathaniel G.; Thompson, David M.; Elias, Edwin; Wang, Ping; Rosati, Julie D.; Roberts, Tiffany M.

2011-01-01

Using Delft3D, a Chandeleur Island model was constructed to examine the sediment-transport patterns and morphodynamic change caused by Hurricane Katrina and similar storm events. The model setup included a coarse Gulf of Mexico domain and a nested finer-resolution Chandeleur Island domain. The finer-resolution domain resolved morphodynamic processes driven by storms and tides. A sensitivity analysis of the simulated morphodynamic response was performed to investigate the effects of variations in surge levels. The Chandeleur morphodynamic model reproduced several important features that matched observed morphodynamic changes. A simulation of bathymetric change driven by storm surge alone (no waves) along the central portion of the Chandeleur Islands showed (1) a general landward retreat and lowering of the island chain and (2) multiple breaches that increased the degree of island dissection. The locations of many of the breaches correspond with the low-lying or narrow sections of the initial bathymetry. The major part of the morphological change occurred prior to the peak of the surge when overtopping of the islands produced a strong water-level gradient and induced significant flow velocities.

Analysis of improved government geological map information for mineral exploration: Incorporating efficiency, productivity, effectiveness, and risk considerations

USGS Publications Warehouse

Bernknopf, R.L.; Wein, A.M.; St-Onge, M. R.; Lucas, S.B.

2007-01-01

This bulletin/professional paper focuses on the value of geoscientific information and knowledge, as provided in published government bedrock geological maps, to the mineral exploration sector. An economic model is developed that uses an attribute- ranking approach to convert geological maps into domains of mineral favourability. Information about known deposits in these (or analogous) favourability domains allow the calculation of exploration search statistics that provide input into measures of exploration efficiency, productivity, effectiveness, risk, and cost stemming from the use of the published geological maps. Two case studies, the Flin Flon Belt (Manitoba and Saskatchewan) and the south Baffin Island area (Nunavut), demonstrate that updated, finer resolution maps can be used to identify more exploration campaign options, and campaigns thats are more efficient, more effective, and less risky than old, coarser resolution maps when used as a guide for mineral exploration. The Flin Flon Belt study illustrates that an updated, coarser resolution bedrock map enables improved mineral exploration efficiency, productivity, and effectiveness by locating 60% more targets and supporting an exploration campaign that is 44% more efficient. Refining the map resolution provides an additional 17% reduction in search effort across all favourable domains and a 55% reduction in search effort in the most favourable domain. The south Baffin Island case study projects a 40% increase in expected targets and a 27% reduction in search effort when the updated, finer resolution map is used in lieu of the old, coarser resolution map. On southern Baffin Island, the economic value of the up dated map ranges from CAN$2.28 million to CAN$15.21 million, which can be compared to the CAN$1.86 million that it cost to produce the map (a multiplier effect of up to eight).

Air Quality Science and Regulatory Efforts Require Geostationary Satellite Measurements

NASA Technical Reports Server (NTRS)

Pickering, Kenneth E.; Allen, D. J.; Stehr, J. W.

2006-01-01

Air quality scientists and regulatory agencies would benefit from the high spatial and temporal resolution trace gas and aerosol data that could be provided by instruments on a geostationary platform. More detailed time-resolved data from a geostationary platform could be used in tracking regional transport and in evaluating mesoscale air quality model performance in terms of photochemical evolution throughout the day. The diurnal cycle of photochemical pollutants is currently missing from the data provided by the current generation of atmospheric chemistry satellites which provide only one measurement per day. Often peak surface ozone mixing ratios are reached much earlier in the day during major regional pollution episodes than during local episodes due to downward mixing of ozone that had been transported above the boundary layer overnight. The regional air quality models often do not simulate this downward mixing well enough and underestimate surface ozone in regional episodes. Having high time-resolution geostationary data will make it possible to determine the magnitude of this lower-and mid-tropospheric transport that contributes to peak eight-hour average ozone and 24-hour average PM2.5 concentrations. We will show ozone and PM(sub 2.5) episodes from the CMAQ model and suggest ways in which geostationary satellite data would improve air quality forecasting. Current regulatory modeling is typically being performed at 12 km horizontal resolution. State and regional air quality regulators in regions with complex topography and/or land-sea breezes are anxious to move to 4-km or finer resolution simulations. Geostationary data at these or finer resolutions will be useful in evaluating such models.

Development and Application of a Process-based River System Model at a Continental Scale

NASA Astrophysics Data System (ADS)

Kim, S. S. H.; Dutta, D.; Vaze, J.; Hughes, J. D.; Yang, A.; Teng, J.

2014-12-01

Existing global and continental scale river models, mainly designed for integrating with global climate model, are of very course spatial resolutions and they lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing streamflow forecast at fine spatial resolution and water accounts at sub-catchment levels, which are important for water resources planning and management at regional and national scale. A large-scale river system model has been developed and implemented for water accounting in Australia as part of the Water Information Research and Development Alliance between Australia's Bureau of Meteorology (BoM) and CSIRO. The model, developed using node-link architecture, includes all major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. It includes an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. An auto-calibration tool has been built within the modelling system to automatically calibrate the model in large river systems using Shuffled Complex Evolution optimiser and user-defined objective functions. The auto-calibration tool makes the model computationally efficient and practical for large basin applications. The model has been implemented in several large basins in Australia including the Murray-Darling Basin, covering more than 2 million km2. The results of calibration and validation of the model shows highly satisfactory performance. The model has been operalisationalised in BoM for producing various fluxes and stores for national water accounting. This paper introduces this newly developed river system model describing the conceptual hydrological framework, methods used for representing different hydrological processes in the model and the results and evaluation of the model performance. The operational implementation of the model for water accounting is discussed.

Identification and simulation of space-time variability of past hydrological drought events in the Limpopo river basin, Southern Africa

NASA Astrophysics Data System (ADS)

Trambauer, P.; Maskey, S.; Werner, M.; Pappenberger, F.; van Beek, L. P. H.; Uhlenbrook, S.

2014-03-01

Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer resolution version (0.05° x 0.05°) of the continental scale hydrological model PCR-GLOBWB was set up for the Limpopo river basin, one of the most water stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse droughts in the Limpopo river basin in the period 1979-2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily time scale for the entire basin. PCR-GLOBWB was forced with daily precipitation, temperature and other meteorological variables obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI) were also computed for different aggregation periods. Results show that a carefully set up process-based model that makes use of the best available input data can successfully identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of droughts/floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6, SPI-12) is found to be a useful measure for identifying hydrological droughts in the Limpopo river basin. Additionally, it is possible to make a characterisation of the drought severity, indicated by its duration and intensity.

A data fusion approach for mapping daily evapotranspiration at field scale

USDA-ARS?s Scientific Manuscript database

The capability for mapping water consumption over cropped landscapes on a daily and seasonal basis is increasingly relevant given forecasted scenarios of reduced water availability. Prognostic modeling of water losses to the atmosphere, or evapotranspiration (ET), at field or finer scales in agricul...

Globalization: Ecological consequences of global-scale connectivity in people, resources and information

USDA-ARS?s Scientific Manuscript database

Globalization is a phenomenon affecting all facets of the Earth System. Within the context of ecological systems, it is becoming increasingly apparent that global connectivity among terrestrial systems, the atmosphere, and oceans is driving many ecological dynamics at finer scales and pushing thresh...

Establishing an Operational Data System for Surface Currents Derived from Satellite Altimeters and Scatterometers; Pilot Study for the Tropical Pacific

NASA Astrophysics Data System (ADS)

Lagerloef, G. S.; Cheney, R.; Mitchum, G. T.

2001-12-01

We are initiating a pilot processing system and data center to provide operational ocean surface velocity fields from satellite altimeter and vector wind data. The team includes the above authors plus M. Bourassa (FSU), V.Kousky (NOAA/NCEP), J.Polovina (NOAA/NMFS/Hawaii CoastWatch), R.Legeckis (NOAA/NESDIS), G. Jacobs (NRL), F. Bonjean (ESR), E.Johnson (ESR) and J.Gunn (ESR). Methods to derive surface currents are the outcome of several years of NASA sponsored research and the pilot project will transition that capability to operational oceanographic applications. The regional focus will be the tropical Pacific. Data applications include large scale climate diagnostics and prediction, fisheries management and recruitment, monitoring debris drift, larvae drift, oil spills, fronts and eddies. Additional uses for search and rescue, naval and maritime operations will be investigated. The pilot study will produce velocity maps to be updated on a weekly basis initially, with a goal for eventual 2-day maximum delay from time of satellite measurement. Grid resolution will be 100 km for the basin scale, and finer resolution in the vicinity of the Pacific Islands. Various illustrations of the velocity maps and their applications will be presented. The project's goal is to leave in place an automated system running at NOAA/NESDIS, with an established user clientele and open Internet data access.

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa

PubMed Central

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F.; Beale, Colin M.

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation. PMID:25915899

NOAA Coral Reef Watch: Decision Support Tools for Coral Reef Managers

NASA Astrophysics Data System (ADS)

Rauenzahn, J.; Eakin, C.; Skirving, W. J.; Burgess, T.; Christensen, T.; Heron, S. F.; Li, J.; Liu, G.; Morgan, J.; Nim, C.; Parker, B. A.; Strong, A. E.

2010-12-01

A multitude of natural and anthropogenic stressors exert substantial influence on coral reef ecosystems and contribute to bleaching events, slower coral growth, infectious disease outbreaks, and mortality. Satellite-based observations can monitor, at a global scale, environmental conditions that influence both short-term and long-term coral reef ecosystem health. From research to operations, NOAA Coral Reef Watch (CRW) incorporates paleoclimatic, in situ, and satellite-based biogeophysical data to provide near-real-time and forecast information and tools to help managers, researchers, and other stakeholders interpret coral health and stress. CRW has developed an operational, near-real-time product suite that includes sea surface temperature (SST), SST time series data, SST anomaly charts, coral bleaching HotSpots, and Degree Heating Weeks (DHW). Bi-weekly global SST analyses are based on operational nighttime-only SST at 50-km resolution. CRW is working to develop high-resolution products to better address thermal stress on finer scales and is applying climate models to develop seasonal outlooks of coral bleaching. Automated Satellite Bleaching Alerts (SBAs), available at Virtual Stations worldwide, provide the only global early-warning system to notify managers of changing reef environmental conditions. Currently, CRW is collaborating with numerous domestic and international partners to develop new tools to address ocean acidification, infectious diseases of corals, combining light and temperature to detect coral photosystem stress, and other parameters.

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa.

PubMed

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F; Beale, Colin M

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation.

Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

NASA Astrophysics Data System (ADS)

Xu, Y.; Wang, L.

2017-12-01

Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.

Impacts of high resolution model downscaling in coastal regions

NASA Astrophysics Data System (ADS)

Bricheno, Lucy; Wolf, Judith

2013-04-01

With model development and cheaper computational resources ocean forecasts are becoming readily available, high resolution coastal forecasting is now a reality. This can only be achieved, however, by downscaling global or basin-scale products such as the MyOcean reanalyses and forecasts. These model products have resolution ranging from 1/16th - 1/4 degree, which are often insufficient for coastal scales, but can provide initialisation and boundary data. We present applications of downscaling the MyOcean products for use in shelf-seas and the nearshore. We will address the question 'Do coastal predictions improve with higher resolution modelling?' with a few focused examples, while also discussing what is meant by an improved result. Increasing resolution appears to be an obvious route for getting more accurate forecasts in operational coastal models. However, when models resolve finer scales, this may lead to the introduction of high-frequency variability which is not necessarily deterministic. Thus a flow may appear more realistic by generating eddies but the simple statistics like rms error and correlation may become less good because the model variability is not exactly in phase with the observations (Hoffman et al., 1995). By deciding on a specific process to simulate (rather than concentrating on reducing rms error) we can better assess the improvements gained by downscaling. In this work we will select two processes which are dominant in our case-study site: Liverpool Bay. Firstly we consider the magnitude and timing of a peak in tide-surge elevations, by separating out the event into timing (or displacement) and intensity (or amplitude) errors. The model can thus be evaluated on how well it predicts the timing and magnitude of the surge. The second important characteristic of Liverpool Bay is the position of the freshwater front. To evaluate model performance in this case, the location, sharpness, and temperature difference across the front will be considered. We will show that by using intelligent metrics designed with a physical process in mind, we can learn more about model performance than by considering 'bulk' statistics alone. R. M. Hoffman and Z. Liu and J-F. Louic and C. Grassotti (1995) 'Distortion Representation of Forecast Errors' Monthly Weather Review 123: 2758-2770

Probing the Inelastic Interactions in Molecular Junctions by Scanning Tunneling Microscope

NASA Astrophysics Data System (ADS)

Xu, Chen

With a sub-Kelvin scanning tunneling microscope, the energy resolution of spectroscopy is improved dramatically. Detailed studies of finer features of spectrum become possible. The asymmetry in the line shape of carbon monoxide vibrational spectra is observed to correlate with the couplings of the molecule to the tip and substrates. The spin-vibronic coupling in the molecular junctions is revisited with two metal phthalocyanine molecules, unveiling sharp spin-vibronic peaks. Finally, thanks to the improved spectrum resolution, the bonding structure of the acyclic compounds molecules is surveyed with STM inelastic tunneling probe, expanding the capability of the innovative high resolution imaging technique.

Skin Friction Reduction Through Large-Scale Forcing

NASA Astrophysics Data System (ADS)

Bhatt, Shibani; Artham, Sravan; Gnanamanickam, Ebenezer

2017-11-01

Flow structures in a turbulent boundary layer larger than an integral length scale (δ), referred to as large-scales, interact with the finer scales in a non-linear manner. By targeting these large-scales and exploiting this non-linear interaction wall shear stress (WSS) reduction of over 10% has been achieved. The plane wall jet (PWJ), a boundary layer which has highly energetic large-scales that become turbulent independent of the near-wall finer scales, is the chosen model flow field. It's unique configuration allows for the independent control of the large-scales through acoustic forcing. Perturbation wavelengths from about 1 δ to 14 δ were considered with a reduction in WSS for all wavelengths considered. This reduction, over a large subset of the wavelengths, scales with both inner and outer variables indicating a mixed scaling to the underlying physics, while also showing dependence on the PWJ global properties. A triple decomposition of the velocity fields shows an increase in coherence due to forcing with a clear organization of the small scale turbulence with respect to the introduced large-scale. The maximum reduction in WSS occurs when the introduced large-scale acts in a manner so as to reduce the turbulent activity in the very near wall region. This material is based upon work supported by the Air Force Office of Scientific Research under Award Number FA9550-16-1-0194 monitored by Dr. Douglas Smith.

Plasma Irregularities on the Leading and Trailing Edges of Polar Cap Patches

NASA Astrophysics Data System (ADS)

Lamarche, L. J.; Varney, R. H.; Gillies, R.; Chartier, A.; Mitchell, C. N.

2017-12-01

Plasma irregularities in the polar cap have often been attributed to the gradient drift instability (GDI). Traditional fluid theories of GDI predicts irregularity growth only on the trailing edge of polar patches, where the plasma density gradient is parallel to the plasma drift velocity, however many observations show irregularities also form on the leading edge of patches. We consider decameter-scale irregularities detected by polar-latitude SuperDARN (Super Dual Auroral Radar Network) radars with any relationship between the background density gradients and drift velocity. Global electron density from the Multi-Instrument Data Analysis System (MIDAS), a GPS tomography routine, is used to provide context for where irregularities are observed relative to polar patches and finer-scale background density gradients are found from 3D imaging from both the North and Canada faces of the Resolute Bay Incoherent Scatter Radars (RISR-N and RISR-C) jointly. Shear-based instabilities are considered as mechanisms by which plasma irregularities could form on the leading edge of patches. Theoretical predictions of instability growth from both GDI and shear instabilities are compared with irregularity observations for the October 13, 2016 storm.

Charge Sharing and Charge Loss in a Cadmium-Zinc-Telluride Fine-Pixel Detector Array

NASA Technical Reports Server (NTRS)

Gaskin, J. A.; Sharma, D. P.; Ramsey, B. D.; Six, N. Frank (Technical Monitor)

2002-01-01

Because of its high atomic number, room temperature operation, low noise, and high spatial resolution a Cadmium-Zinc-Telluride (CZT) multi-pixel detector is ideal for hard x-ray astrophysical observation. As part of on-going research at MSFC (Marshall Space Flight Center) to develop multi-pixel CdZnTe detectors for this purpose, we have measured charge sharing and charge loss for a 4x4 (750micron pitch), lmm thick pixel array and modeled these results using a Monte-Carlo simulation. This model was then used to predict the amount of charge sharing for a much finer pixel array (with a 300micron pitch). Future work will enable us to compare the simulated results for the finer array to measured values.

Observation-Corrected Precipitation Estimates in GEOS-5

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing

2014-01-01

Several GEOS-5 applications, including the GEOS-5 seasonal forecasting system and the MERRA-Land data product, rely on global precipitation data that have been corrected with satellite and or gauge-based precipitation observations. This document describes the methodology used to generate the corrected precipitation estimates and their use in GEOS-5 applications. The corrected precipitation estimates are derived by disaggregating publicly available, observationally based, global precipitation products from daily or pentad totals to hourly accumulations using background precipitation estimates from the GEOS-5 atmospheric data assimilation system. Depending on the specific combination of the observational precipitation product and the GEOS-5 background estimates, the observational product may also be downscaled in space. The resulting corrected precipitation data product is at the finer temporal and spatial resolution of the GEOS-5 background and matches the observed precipitation at the coarser scale of the observational product, separately for each day (or pentad) and each grid cell.

Near term climate projections for invasive species distributions

USGS Publications Warehouse

Jarnevich, C.S.; Stohlgren, T.J.

2009-01-01

Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas. ?? 2008 Springer Science+Business Media B.V.

A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model

NASA Astrophysics Data System (ADS)

Abbaspour, K. C.; Rouholahnejad, E.; Vaghefi, S.; Srinivasan, R.; Yang, H.; Kløve, B.

2015-05-01

A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.

Improved microgrid arrangement for integrated imaging polarimeters.

PubMed

LeMaster, Daniel A; Hirakawa, Keigo

2014-04-01

For almost 20 years, microgrid polarimetric imaging systems have been built using a 2×2 repeating pattern of polarization analyzers. In this Letter, we show that superior spatial resolution is achieved over this 2×2 case when the analyzers are arranged in a 2×4 repeating pattern. This unconventional result, in which a more distributed sampling pattern results in finer spatial resolution, is also achieved without affecting the conditioning of the polarimetric data-reduction matrix. Proof is provided theoretically and through Stokes image reconstruction of synthesized data.

Satellite microwave detection of contrasting changes in surface inundation across pan-Arctic permafrost zones

NASA Astrophysics Data System (ADS)

Watts, J.; Kimball, J. S.; Jones, L. A.; Schroeder, R.; McDonald, K. C.

2012-12-01

Surface water inundation in the Arctic is concomitant with soil permafrost and strongly influences land-atmosphere water, energy and carbon (CO2, CH4) exchange, and plant community structure. We examine recent (2003-2010) surface water inundation patterns across the pan-Arctic (≥ 50 deg.N) and within major permafrost zones using satellite passive microwave remote sensing retrievals of fractional open water extent (Fw) derived from Advanced Microwave Scanning Radiometer for EOS (AMSR-E) 18.7 and 23.8 GHz brightness temperatures. The AMSR-E Fw retrievals are insensitive to atmosphere contamination and solar illumination effects, enabling daily Fw monitoring across the Arctic. The Fw retrievals are sensitive to sub-grid scale open water inundation area, including lakes and wetlands, within the relatively coarse (~25-km resolution) satellite footprint. A forward model error sensitivity analysis indicates that total Fw retrieval uncertainty is within ±4.1% (RMSE), and AMSR-E Fw compares favorably (0.71 < R2 < 0.84) with alternative static open water maps derived from finer scale (30-m to 250-m resolution) Landsat, MODIS and SRTM radar-based products. The Fw retrievals also show dynamic seasonal and annual variability in surface inundation that corresponds (0.71 < R < 0.87) with regional wet/dry cycles inferred from basin discharge records, including Yukon, Mackenzie, Ob, Yenisei, and Lena basins. A regional change analysis of the 8-yr AMSR-E record shows no significant trend in pan-Arctic wide Fw, and instead reveals contrasting inundation changes within permafrost zones. Widespread Fw wetting is observed within continuous (92% of grid cells with significant trend show wetting; p < 0.1) and discontinuous (82%) permafrost zones, while areas with sporadic/isolated permafrost show widespread (71%) Fw drying. These results are consistent with previous studies showing evidence of changes in regional surface hydrology influenced by permafrost degradation under recent climate warming. Changes in Fw may also be linked to shifts in regional precipitation patterns and a lengthening non-frozen season. Regional changes observed in the AMSR-E Fw record compliment finer-scale permafrost monitoring efforts and documented variability in surface inundation extent may help constrain pan-Arctic lake and wetland CO2, CH4 emission estimates. This work was supported under the Jet Propulsion Laboratory, California Institute of Technology under contract to the National Aeronautics and Space Administration, NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) programs.

Impact of Resolution on Simulation of Closed Mesoscale Cellular Convection Identified by Dynamically Guided Watershed Segmentation

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

Martini, Matus N.; Gustafson, William I.; Yang, Qing

2014-11-18

Organized mesoscale cellular convection (MCC) is a common feature of marine stratocumulus that forms in response to a balance between mesoscale dynamics and smaller scale processes such as cloud radiative cooling and microphysics. We use the Weather Research and Forecasting model with chemistry (WRF-Chem) and fully coupled cloud-aerosol interactions to simulate marine low clouds during the VOCALS-REx campaign over the southeast Pacific. A suite of experiments with 3- and 9-km grid spacing indicates resolution-dependent behavior. The simulations with finer grid spacing have smaller liquid water paths and cloud fractions, while cloud tops are higher. The observed diurnal cycle is reasonablymore » well simulated. To isolate organized MCC characteristics we develop a new automated method, which uses a variation of the watershed segmentation technique that combines the detection of cloud boundaries with a test for coincident vertical velocity characteristics. This ensures that the detected cloud fields are dynamically consistent for closed MCC, the most common MCC type over the VOCALS-REx region. We demonstrate that the 3-km simulation is able to reproduce the scaling between horizontal cell size and boundary layer height seen in satellite observations. However, the 9-km simulation is unable to resolve smaller circulations corresponding to shallower boundary layers, instead producing invariant MCC horizontal scale for all simulated boundary layers depths. The results imply that climate models with grid spacing of roughly 3 km or smaller may be needed to properly simulate the MCC structure in the marine stratocumulus regions.« less

A Parameter Estimation Scheme for Multiscale Kalman Smoother (MKS) Algorithm Used in Precipitation Data Fusion

NASA Technical Reports Server (NTRS)

Wang, Shugong; Liang, Xu

2013-01-01

A new approach is presented in this paper to effectively obtain parameter estimations for the Multiscale Kalman Smoother (MKS) algorithm. This new approach has demonstrated promising potentials in deriving better data products based on data of different spatial scales and precisions. Our new approach employs a multi-objective (MO) parameter estimation scheme (called MO scheme hereafter), rather than using the conventional maximum likelihood scheme (called ML scheme) to estimate the MKS parameters. Unlike the ML scheme, the MO scheme is not simply built on strict statistical assumptions related to prediction errors and observation errors, rather, it directly associates the fused data of multiple scales with multiple objective functions in searching best parameter estimations for MKS through optimization. In the MO scheme, objective functions are defined to facilitate consistency among the fused data at multiscales and the input data at their original scales in terms of spatial patterns and magnitudes. The new approach is evaluated through a Monte Carlo experiment and a series of comparison analyses using synthetic precipitation data. Our results show that the MKS fused precipitation performs better using the MO scheme than that using the ML scheme. Particularly, improvements are significant compared to that using the ML scheme for the fused precipitation associated with fine spatial resolutions. This is mainly due to having more criteria and constraints involved in the MO scheme than those included in the ML scheme. The weakness of the original ML scheme that blindly puts more weights onto the data associated with finer resolutions is overcome in our new approach.

Using regional bird density distribution models to evaluate protected area networks and inform conservation planning

Treesearch

John D. Alexander; Jaime L. Stephens; Sam Veloz; Leo Salas; Josée S. Rousseau; C. John Ralph; Daniel A. Sarr

2017-01-01

As data about populations of indicator species become available, proactive strategies that improve representation of biological diversity within protected area networks should consider finer-scaled evaluations, especially in regions identified as important through course-scale analyses. We use density distribution models derived from a robust regional bird...

Indicators of climate change in Idaho: An assessment framework for coupling biophysical change and social perception

USDA-ARS?s Scientific Manuscript database

Climate change is well documented at the global scale, but local and regional changes are not as well understood. Finer, local-to-regional scale information is needed for creating specific, place-based planning and adaption efforts. Here we detail the development of an indicator-focused climate chan...

Socioeconomic evaluation of broad-scale land management strategies.

Treesearch

Lisa K. Crone; Richard W. Haynes

2001-01-01

This paper examines the socioeconomic effects of alternative management strategies for Forest Service and Bureau of Land Management lands in the interior Columbia basin. From a broad-scale perspective, there is little impact or variation between alternatives in terms of changes in total economic activity or social conditions in the region. However, adopting a finer...

Description and evaluation of the Earth System Regional Climate Model (RegCM-ES)

NASA Astrophysics Data System (ADS)

Farneti, Riccardo; Sitz, Lina; Di Sante, Fabio; Fuentes-Franco, Ramon; Coppola, Erika; Mariotti, Laura; Reale, Marco; Sannino, Gianmaria; Barreiro, Marcelo; Nogherotto, Rita; Giuliani, Graziano; Graffino, Giorgio; Solidoro, Cosimo; Giorgi, Filippo

2017-04-01

The increasing availability of satellite remote sensing data, of high temporal frequency and spatial resolution, has provided a new and enhanced view of the global ocean and atmosphere, revealing strong air-sea coupling processes throughout the ocean basins. In order to obtain an accurate representation and better understanding of the climate system, its variability and change, the inclusion of all mechanisms of interaction among the different sub-components, at high temporal and spatial resolution, becomes ever more desirable. Recently, global coupled models have been able to progressively refine their horizontal resolution to attempt to resolve smaller-scale processes. However, regional coupled ocean-atmosphere models can achieve even finer resolutions and provide additional information on the mechanisms of air-sea interactions and feedbacks. Here we describe a new, state-of-the-art, Earth System Regional Climate Model (RegCM-ES). RegCM-ES presently includes the coupling between atmosphere, ocean, land surface and sea-ice components, as well as an hydrological and ocean biogeochemistry model. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains. RegCM-ES has shown improvements in the representation of precipitation and SST fields over the tested domains, as well as realistic representations of coupled air-sea processes and interactions. The RegCM-ES model, which can be easily implemented over any regional domain of interest, is open source making it suitable for usage by the large scientific community.

High-resolution mapping of motor vehicle carbon dioxide emissions

NASA Astrophysics Data System (ADS)

McDonald, Brian C.; McBride, Zoe C.; Martin, Elliot W.; Harley, Robert A.

2014-05-01

A fuel-based inventory for vehicle emissions is presented for carbon dioxide (CO2) and mapped at various spatial resolutions (10 km, 4 km, 1 km, and 500 m) using fuel sales and traffic count data. The mapping is done separately for gasoline-powered vehicles and heavy-duty diesel trucks. Emission estimates from this study are compared with the Emissions Database for Global Atmospheric Research (EDGAR) and VULCAN. All three inventories agree at the national level within 5%. EDGAR uses road density as a surrogate to apportion vehicle emissions, which leads to 20-80% overestimates of on-road CO2 emissions in the largest U.S. cities. High-resolution emission maps are presented for Los Angeles, New York City, San Francisco-San Jose, Houston, and Dallas-Fort Worth. Sharp emission gradients that exist near major highways are not apparent when emissions are mapped at 10 km resolution. High CO2 emission fluxes over highways become apparent at grid resolutions of 1 km and finer. Temporal variations in vehicle emissions are characterized using extensive day- and time-specific traffic count data and are described over diurnal, day of week, and seasonal time scales. Clear differences are observed when comparing light- and heavy-duty vehicle traffic patterns and comparing urban and rural areas. Decadal emission trends were analyzed from 2000 to 2007 when traffic volumes were increasing and a more recent period (2007-2010) when traffic volumes declined due to recession. We found large nonuniform changes in on-road CO2 emissions over a period of 5 years, highlighting the importance of timely updates to motor vehicle emission inventories.

A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems

NASA Astrophysics Data System (ADS)

Fairbanks, Hillary R.; Doostan, Alireza; Ketelsen, Christian; Iaccarino, Gianluca

2017-07-01

Multilevel Monte Carlo (MLMC) is a recently proposed variation of Monte Carlo (MC) simulation that achieves variance reduction by simulating the governing equations on a series of spatial (or temporal) grids with increasing resolution. Instead of directly employing the fine grid solutions, MLMC estimates the expectation of the quantity of interest from the coarsest grid solutions as well as differences between each two consecutive grid solutions. When the differences corresponding to finer grids become smaller, hence less variable, fewer MC realizations of finer grid solutions are needed to compute the difference expectations, thus leading to a reduction in the overall work. This paper presents an extension of MLMC, referred to as multilevel control variates (MLCV), where a low-rank approximation to the solution on each grid, obtained primarily based on coarser grid solutions, is used as a control variate for estimating the expectations involved in MLMC. Cost estimates as well as numerical examples are presented to demonstrate the advantage of this new MLCV approach over the standard MLMC when the solution of interest admits a low-rank approximation and the cost of simulating finer grids grows fast.

Seltzer_et_al_2016

EPA Pesticide Factsheets

This dataset supports the modeling study of Seltzer et al. (2016) published in Atmospheric Environment. In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000-2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method??s use for future air quality projections.This dataset is associated with the following publication:Seltzer, K., C

Delineating wetland catchments and modeling hydrologic ...

EPA Pesticide Factsheets

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling–spilling–merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that

Disaggregating census data for population mapping using random forests with remotely-sensed and ancillary data.

PubMed

Stevens, Forrest R; Gaughan, Andrea E; Linard, Catherine; Tatem, Andrew J

2015-01-01

High resolution, contemporary data on human population distributions are vital for measuring impacts of population growth, monitoring human-environment interactions and for planning and policy development. Many methods are used to disaggregate census data and predict population densities for finer scale, gridded population data sets. We present a new semi-automated dasymetric modeling approach that incorporates detailed census and ancillary data in a flexible, "Random Forest" estimation technique. We outline the combination of widely available, remotely-sensed and geospatial data that contribute to the modeled dasymetric weights and then use the Random Forest model to generate a gridded prediction of population density at ~100 m spatial resolution. This prediction layer is then used as the weighting surface to perform dasymetric redistribution of the census counts at a country level. As a case study we compare the new algorithm and its products for three countries (Vietnam, Cambodia, and Kenya) with other common gridded population data production methodologies. We discuss the advantages of the new method and increases over the accuracy and flexibility of those previous approaches. Finally, we outline how this algorithm will be extended to provide freely-available gridded population data sets for Africa, Asia and Latin America.

Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimations over Continental South America

NASA Technical Reports Server (NTRS)

Vila, Daniel; deGoncalves, Luis Gustavo; Toll, David L.; Rozante, Jose Roberto

2008-01-01

This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.

Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

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.

The Solomon Sea eddy activity from a 1/36° regional model

NASA Astrophysics Data System (ADS)

Djath, Bughsin; Babonneix, Antoine; Gourdeau, Lionel; Marin, Frédéric; Verron, Jacques

2013-04-01

In the South West Pacific, the Solomon Sea exhibits the highest levels of eddy kinetic energy but relatively little is known about the eddy activity in this region. This Sea is directly influenced by a monsoonal regime and ENSO variability, and occupies a strategical location as the Western Boundary Currents exiting it are known to feed the warm pool and to be the principal sources of the Equatorial UnderCurrent. During their transit in the Solomon Sea, meso-scale eddies are suspected to notably interact and influence these water masses. The goal of this study is to give an exhaustive description of this eddy activity. A dual approach, based both on altimetric data and high resolution modeling, has then been chosen for this purpose. First, an algorithm is applied on nearly 20 years of 1/3° x 1/3° gridded SLA maps (provided by the AVISO project). This allows eddies to be automatically detected and tracked, thus providing some basic eddy properties. The preliminary results show that two main and distinct types of eddies are detected. Eddies in the north-eastern part shows a variability associated with the mean structure, while those in the southern part are associated with generation/propagation processes. However, the resolution of the AVISO dataset is not very well suited to observe fine structures and to match with the numerous islands bordering the Solomon Sea. For this reason, we will confront these observations with the outputs of a 1/36° resolution realistic model of the Solomon Sea. The high resolution numerical model (1/36°) indeed permits to reproduce very fine scale features, such as eddies and filaments. The model is two-way embedded in a 1/12° regional model which is itself one-way embedded in the DRAKKAR 1/12° global model. The NEMO code is used as well as the AGRIF software for model nestings. Validation is realized by comparison with AVISO observations and available in situ data. In preparing the future wide-swath altimetric SWOT mission that is expected to provide observations of small-scale sea level variability, spectral analysis is performed from the 1/36° resolution realistic model in order to characterize the finer scale signals in the Solomon sea region. The preliminary SSH spectral analysis shows a k-4 slope, in good agreement with the suface quasigeostrophic (SQG) turbulence theory. Keywords: Solomon Sea; meso-scale activity; eddy detection, tracking and properties; wavenumber spectrum.

On the impact of the resolution on the surface and subsurface Eastern Tropical Atlantic warm bias

NASA Astrophysics Data System (ADS)

Martín-Rey, Marta; Lazar, Alban

2016-04-01

The tropical variability has a great importance for the climate of adjacent areas. Its sea surface temperature anomalies (SSTA) affect in particular the Brazilian Nordeste and the Sahelian region, as well as the tropical Pacific or the Euro-Atlantic sector. Nevertheless, the state-of the art climate models exhibits very large systematic errors in reproducing the seasonal cycle and inter-annual variability in the equatorial and coastal Africa upwelling zones (up to several °C for SST). Theses biases exist already, in smaller proportions though, in forced ocean models (several 1/10th of °C), and affect not only the mixed layer but also the whole thermocline. Here, we present an analysis of the impact of horizontal and vertical resolution changes on these biases. Three different DRAKKAR NEMO OGCM simulations have been analysed, associated to the same forcing set (DFS4.4) with different grid resolutions: "REF" for reference (1/4°, 46 vertical levels), "HH" with a finer horizontal grid (1/12°, 46 v.l.) and "HV" with a finer vertical grid (1/4°, 75 v.l.). At the surface, a more realistic seasonal SST cycle is produced in HH in the three upwellings, where the warm bias decreases (by 10% - 20%) during boreal spring and summer. A notable result is that increasing vertical resolution in HV causes a shift (in advance) of the upwelling SST seasonal cycles. In order to better understand these results, we estimate the three upwelling subsurface temperature errors, using various in-situ datasets, and provide thus a three-dimensional view of the biases.

Influence of grid resolution in fluid-model simulation of nanosecond dielectric barrier discharge plasma actuator

NASA Astrophysics Data System (ADS)

Hua, Weizhuo; Fukagata, Koji

2018-04-01

Two-dimensional numerical simulation of a surface dielectric barrier discharge (SDBD) plasma actuator, driven by a nanosecond voltage pulse, is conducted. A special focus is laid upon the influence of grid resolution on the computational result. It is found that the computational result is not very sensitive to the streamwise grid spacing, whereas the wall-normal grid spacing has a critical influence. In particular, the computed propagation velocity changes discontinuously around the wall-normal grid spacing about 2 μm due to a qualitative change of discharge structure. The present result suggests that a computational grid finer than that was used in most of previous studies is required to correctly capture the structure and dynamics of streamer: when a positive nanosecond voltage pulse is applied to the upper electrode, a streamer forms in the vicinity of upper electrode and propagates along the dielectric surface with a maximum propagation velocity of 2 × 108 cm/s, and a gap with low electron and ion density (i.e., plasma sheath) exists between the streamer and dielectric surface. Difference between the results obtained using the finer and the coarser grid is discussed in detail in terms of the electron transport at a position near the surface. When the finer grid is used, the low electron density near the surface is caused by the absence of ionization avalanche: in that region, the electrons generated by ionization is compensated by drift-diffusion flux. In contrast, when the coarser grid is used, underestimated drift-diffusion flux cannot compensate the electrons generated by ionization, and it leads to an incorrect increase of electron density.

Proof of Concept for an Approach to a Finer Resolution Inventory

Treesearch

Chris J. Cieszewski; Kim Iles; Roger C. Lowe; Michal Zasada

2005-01-01

This report presents a proof of concept for a statistical framework to develop a timely, accurate, and unbiased fiber supply assessment in the State of Georgia, U.S.A. The proposed approach is based on using various data sources and modeling techniques to calibrate satellite image-based statewide stand lists, which provide initial estimates for a State inventory on a...

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

Cololla, P.

This review describes a structured approach to adaptivity. The Automated Mesh Refinement (ARM) algorithms developed by M Berger are described, touching on hyperbolic and parabolic applications. Adaptivity is achieved by overlaying finer grids only in areas flagged by a generalized error criterion. The author discusses some of the issues involved in abutting disparate-resolution grids, and demonstrates that suitable algorithms exist for dissipative as well as hyperbolic systems.

The T-REX valley wind intercomparison project

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

Schmidli, J; Billings, B J; Burton, R

2008-08-07

An accurate simulation of the evolution of the atmospheric boundary layer is very important, as the evolution of the boundary layer sets the stage for many weather phenomena, such as deep convection. Over mountain areas the evolution of the boundary layer is particularly complex, due to the nonlinear interaction between boundary layer turbulence and thermally-induced mesoscale wind systems, such as the slope and valley winds. As the horizontal resolution of operational forecasts progresses to finer and finer resolution, more and more of the thermally-induced mesoscale wind systems can be explicitly resolved, and it is very timely to document the currentmore » state-of-the-art of mesoscale models at simulating the coupled evolution of the mountain boundary layer and the valley wind system. In this paper we present an intercomparison of valley wind simulations for an idealized valley-plain configuration using eight state-of-the-art mesoscale models with a grid spacing of 1 km. Different sets of three-dimensional simulations are used to explore the effects of varying model dynamical cores and physical parameterizations. This intercomparison project was conducted as part of the Terrain-induced Rotor Experiment (T-REX; Grubisic et al., 2008).« less

Focusing X-Ray Telescopes

NASA Technical Reports Server (NTRS)

O'Dell, Stephen; Brissenden, Roger; Davis, William; Elsner, Ronald; Elvis, Martin; Freeman, Mark; Gaetz, Terrance; Gorenstein, Paul; Gubarev, Mikhall; Jerlus, Diab;

On precise phase difference measurement approach using border stability of detection resolution.

PubMed

Bai, Lina; Su, Xin; Zhou, Wei; Ou, Xiaojuan

2015-01-01

For the precise phase difference measurement, this paper develops an improved dual phase coincidence detection method. The measurement resolution of the digital phase coincidence detection circuits is always limited, for example, only at the nanosecond level. This paper reveals a new way to improve the phase difference measurement precision by using the border stability of the circuit detection fuzzy areas. When a common oscillator signal is used to detect the phase coincidence with the two comparison signals, there will be two detection fuzzy areas for the reason of finite detection resolution surrounding the strict phase coincidence. Border stability of fuzzy areas and the fluctuation difference of the two fuzzy areas can be even finer than the picoseconds level. It is shown that the system resolution obtained only depends on the stability of the circuit measurement resolution which is much better than the measurement device resolution itself.

A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses

USGS Publications Warehouse

Stefanova, Lydia; Misra, Vasubandhu; Chan, Steven; Griffin, Melissa; O'Brien, James J.; Smith, Thomas J.

2012-01-01

We present an analysis of the seasonal, subseasonal, and diurnal variability of rainfall from COAPS Land- Atmosphere Regional Reanalysis for the Southeast at 10-km resolution (CLARReS10). Most of our assessment focuses on the representation of summertime subseasonal and diurnal variability.Summer precipitation in the Southeast United States is a particularly challenging modeling problem because of the variety of regional-scale phenomena, such as sea breeze, thunderstorms and squall lines, which are not adequately resolved in coarse atmospheric reanalyses but contribute significantly to the hydrological budget over the region. We find that the dynamically downscaled reanalyses are in good agreement with station and gridded observations in terms of both the relative seasonal distribution and the diurnal structure of precipitation, although total precipitation amounts tend to be systematically overestimated. The diurnal cycle of summer precipitation in the downscaled reanalyses is in very good agreement with station observations and a clear improvement both over their "parent" reanalyses and over newer-generation reanalyses. The seasonal cycle of precipitation is particularly well simulated in the Florida; this we attribute to the ability of the regional model to provide a more accurate representation of the spatial and temporal structure of finer-scale phenomena such as fronts and sea breezes. Over the northern portion of the domain summer precipitation in the downscaled reanalyses remains, as in the "parent" reanalyses, overestimated. Given the degree of success that dynamical downscaling of reanalyses demonstrates in the simulation of the characteristics of regional precipitation, its favorable comparison to conventional newer-generation reanalyses and its cost-effectiveness, we conclude that for the Southeast United states such downscaling is a viable proxy for high-resolution conventional reanalysis.

Validation of SMAP data using Cosmic-ray Neutron Probes during the SMAPVEX16-IA Campaign

NASA Astrophysics Data System (ADS)

Russell, M. V.

2016-12-01

Global trends in consumptive water-use indicate a growing and unsustainable reliance on water resources. Each year it is estimated that 60 percent of water used for agriculture is wasted through inadequate water conservation, losses in distribution, and inappropriate times and rates of irrigation. Satellite remote sensing offers a variety of water balance datasets (precipitation, evapotranspiration, soil moisture, groundwater storage) to increase the water use efficiency in agricultural systems. In this work, we aim to validate the Soil Moisture Active Passive (SMAP) soil moisture product using the ground based cosmic-ray neutron probe (CRNP) for estimating field scale soil moisture at intermediate spatial scales as part of SMAPVEX16-IA experiment. Typical SMAP calibration and validation has been done using a combination of direct gravimetric sampling and in-situ soil moisture point observations. Although these measurements provide accurate data, it is time consuming and labor intensive to collect data over a 36 by 36 km SMAP pixel. Through a joint effort with rovers provided by the US Army Corps of Engineers and University of Nebraska-Lincoln, we are able to cover the domain in 7 hours. Data from both rovers was combined in order to produce a 1, 3, 9 and 36 km resolution product on the day of 12 SMAP overpasses in May and August 2016. Here we will describe basic QAQC procedures for estimating soil moisture from the dual rover experiment. This will include discussion about calibration, validation, and accounting for conditions such as variable road type and growing vegetation. Lastly, we will compare the calibrated rover and SMAP products. If the products are highly correlated the ground based rovers offer a strategy for collecting finer resolution products that may be used in future downscaling efforts in support of high resolution Land Surface Modeling.

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.

Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data

NASA Astrophysics Data System (ADS)

Higginbottom, Thomas P.; Symeonakis, Elias; Meyer, Hanna; van der Linden, Sebastian

2018-05-01

Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies. Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (<30%), which are areas of concern for environmental monitoring. At finer spatial resolutions, the inclusion of SAR data actually reduced accuracies. Overall, the RFE was able to produce the most accurate model (R2 = 0.8, RMSE = 8.9, at the 120 m pixel scale). For mapping savannah woody cover at the 30 m pixel scale, we suggest that monitoring methodologies continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.

Enhancing PTFs with remotely sensed data for multi-scale soil water retention estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.

2011-03-01

SummaryUse of remotely sensed data products in the earth science and water resources fields is growing due to increasingly easy availability of the data. Traditionally, pedotransfer functions (PTFs) employed for soil hydraulic parameter estimation from other easily available data have used basic soil texture and structure information as inputs. Inclusion of surrogate/supplementary data such as topography and vegetation information has shown some improvement in the PTF's ability to estimate more accurate soil hydraulic parameters. Artificial neural networks (ANNs) are a popular tool for PTF development, and are usually applied across matching spatial scales of inputs and outputs. However, different hydrologic, hydro-climatic, and contaminant transport models require input data at different scales, all of which may not be easily available from existing databases. In such a scenario, it becomes necessary to scale the soil hydraulic parameter values estimated by PTFs to suit the model requirements. Also, uncertainties in the predictions need to be quantified to enable users to gauge the suitability of a particular dataset in their applications. Bayesian Neural Networks (BNNs) inherently provide uncertainty estimates for their outputs due to their utilization of Markov Chain Monte Carlo (MCMC) techniques. In this paper, we present a PTF methodology to estimate soil water retention characteristics built on a Bayesian framework for training of neural networks and utilizing several in situ and remotely sensed datasets jointly. The BNN is also applied across spatial scales to provide fine scale outputs when trained with coarse scale data. Our training data inputs include ground/remotely sensed soil texture, bulk density, elevation, and Leaf Area Index (LAI) at 1 km resolutions, while similar properties measured at a point scale are used as fine scale inputs. The methodology was tested at two different hydro-climatic regions. We also tested the effect of varying the support scale of the training data for the BNNs by sequentially aggregating finer resolution training data to coarser resolutions, and the applicability of the technique to upscaling problems. The BNN outputs are corrected for bias using a non-linear CDF-matching technique. Final results show good promise of the suitability of this Bayesian Neural Network approach for soil hydraulic parameter estimation across spatial scales using ground-, air-, or space-based remotely sensed geophysical parameters. Inclusion of remotely sensed data such as elevation and LAI in addition to in situ soil physical properties improved the estimation capabilities of the BNN-based PTF in certain conditions.

Homogenization of Electromagnetic and Seismic Wavefields for Joint Inverse Modeling

NASA Astrophysics Data System (ADS)

Newman, G. A.; Commer, M.; Petrov, P.; Um, E. S.

2011-12-01

A significant obstacle in developing a robust joint imaging technology exploiting seismic and electromagnetic (EM) wave fields is the resolution at which these different geophysical measurements sense the subsurface. Imaging of seismic reflection data is an order of magnitude finer in resolution and scale compared to images produced with EM data. A consistent joint image of the subsurface geophysical attributes (velocity, electrical conductivity) requires/demands the different geophysical data types be similar in their resolution of the subsurface. The superior resolution of seismic data results from the fact that the energy propagates as a wave, while propagation of EM energy is diffusive and attenuates with distance. On the other hand, the complexity of the seismic wave field can be a significant problem due to high reflectivity of the subsurface and the generation of multiple scattering events. While seismic wave fields have been very useful in mapping the subsurface for energy resources, too much scattering and too many reflections can lead to difficulties in imaging and interpreting seismic data. To overcome these obstacles a formulation for joint imaging of seismic and EM wave fields is introduced, where each data type is matched in resolution. In order to accomplish this, seismic data are first transformed into the Laplace-Fourier Domain, which changes the modeling of the seismic wave field from wave propagation to diffusion. Though high frequency information (reflectivity) is lost with this transformation, several benefits follow: (1) seismic and EM data can be easily matched in resolution, governed by the same physics of diffusion, (2) standard least squares inversion works well with diffusive type problems including both transformed seismic and EM, (3) joint imaging of seismic and EM data may produce better starting velocity models critical for successful reverse time migration or full waveform imaging of seismic data (non transformed) and (4) possibilities to image across multiple scale lengths, incorporating different types of geophysical data and attributes in the process. Important numerical details of 3D seismic wave field simulation in the Laplace-Fourier domain for both acoustic and elastic cases will also be discussed.

In-situ Fluorometers Reveal High Frequency Dynamics In Dissolved Organic Matter For Urban Rivers

NASA Astrophysics Data System (ADS)

Croghan, D.; Bradley, C.; Khamis, K.; Hannah, D. M.; Sadler, J. P.; Van Loon, A.

2017-12-01

To-date Dissolved Organic Matter (DOM) dynamics have been quantified poorly in urban rivers, despite the substantial water quality issues linked to urbanisation. Research has been hindered by the low temporal resolution of observations and over-reliance on manual sampling which often fail to capture precipitation events and diurnal dynamics. High frequency data are essential to estimate more accurately DOM fluxes/loads and to understand DOM furnishing and transport processes. Recent advances in optical sensor technology, including field deployable in-situ fluorometers, are yielding new high resolution DOM information. However, no consensus regarding the monitoring resolution required for urban systems exists, with no studies monitoring at <15 min time steps. High-frequency monitoring (5 min resolution; 4 week duration) was conducted on a headwater urban stream in Birmingham, UK (N 52.447430 W -1.936715) to determine the optimum temporal resolution for characterization of DOM event dynamics. A through-flow GGNU-30 monitored wavelengths corresponding to tryptophan-like fluorescence (TLF; Peak T1) (Ex 285 nm/ Em 345 nm) and humic-like fluorescence (HLF; Peak C) (Ex 365 nm/Em 490 nm). The results suggest that at base flow TLF and HLF are relatively stable, though episodic DOM inputs can pulse through the system, which may be missed during lower temporal resolution monitoring. High temporal variation occurs during storm events in TLF and HLF intensity: TLF intensity is highest during the rising limb of the hydrograph and can rapidly decline thereafter, indicating the importance of fast flow-path and close proximity sources to TLF dynamics. HLF intensity tracks discharge more closely, but can also quickly decline during high flow events due to dilution effects. Furthermore, the ratio of TLF:HLF when derived at high-frequency provides a useful indication of the presence and type of organic effluents in stream, which aids in the identification of Combined Sewage Overflow releases. Our work highlights the need for future studies to utilise shorter temporal scales than previously used to monitor urban DOM dynamics. The application of higher frequency monitoring enables the identification of finer-scale patterns and subsequently aids in deciphering the sources and pathways controlling urban DOM dynamics.

Darwin's naturalization hypothesis up-close: Intermountain grassland invaders differ morphologically and phenologically from native community dominants

Treesearch

Dean E. Pearson; Yvette K. Ortega; Samantha J. Sears

2012-01-01

Darwin's naturalization hypothesis predicts that successful invaders will tend to differ taxonomically from native species in recipient communities because less related species exhibit lower niche overlap and experience reduced biotic resistance. This hypothesis has garnered substantial support at coarse scales. However, at finer scales, the influence of traits...

Can local adaptation explain varying patterns of herbivory tolerance in a recently introduced woody plant in North America?

USDA-ARS?s Scientific Manuscript database

Trends in tree mortality have been linked to global scale environmental changes, such as extreme drought and heat stress, more frequent and intense fires, and increased episodic outbreaks of insects and pathogens. Finer scale studies have also focused on survival and mortality in response to physiol...

Snow driven Radiative Forcing in High Latitude Areas of Disturbance Using Higher Resolution Albedo Products from Landsat and Sentinel-2

NASA Astrophysics Data System (ADS)

Erb, A.; Li, Z.; Schaaf, C.; Wang, Z.; Rogers, B. M.

2017-12-01

Land surface albedo plays an important role in the surface energy budget and radiative forcing by determining the proportion of absorbed incoming solar radiation available to drive photosynthesis and surface heating. In Arctic regions, albedo is particularly sensitive to land cover and land use change (LCLUC) and modeling efforts have shown it to be the primary driver of effective radiative forcing from the biogeophysical effects of LCLUC. In boreal forests, the effects of these changes are complicated during snow covered periods when newly exposed, highly reflective snow can serve as the primary driver of radiative forcing. In Arctic biomes disturbance scars from fire, pest and harvest can remain in the landscape for long periods of time. As such, understanding the magnitude and persistence of these disturbances, especially in the shoulder seasons, is critical. The Landsat and Sentinel-2 Albedo Products couple 30m and 20m surface reflectances with concurrent 500m BRDF Products from the MODerate resolution Imaging Spectroradiometer (MODIS). The 12 bit radiometric fidelity of Sentinel-2 and Landsat-8 allow for the inclusion of high-quality, unsaturated albedo calculations over snow covered surfaces at scales more compatible with fragmented landscapes. Recent work on the early spring albedo of fire scars has illustrated significant post-fire spatial heterogeneity of burn severity at the landscape scale and highlights the need for a finer spatial resolution albedo record. The increased temporal resolution provided by multiple satellite instruments also allows for a better understanding of albedo dynamics during the dynamic shoulder seasons and in historically difficult high latitude locations where persistent cloud cover limits high quality retrievals. Here we present how changes in the early spring albedo of recent boreal forest disturbance in Alaska and central Canada affects landscape-scale radiative forcing. We take advantage of the long historical Landsat record to examine pre-disturbance albedo trends and to link historical land cover and disturbance history to post-disturbance early spring albedo values. We examine the impact of landscape heterogeneity on albedo in the growing and dormant seasons and quantify the effects of snow exposure changes from over-story canopy loss.

Monitoring Crop Phenology and Growth Stages from Space: Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.; Mladenova, I. E.; Kustas, W. P.; Alfieri, J. G.

2014-12-01

Crop growth stages in concert with weather and soil moisture conditions can have a significant impact on crop yields. In the U.S., crop growth stages and conditions are reported by farmers at the county level. These reports are somewhat subjective and fluctuate between different reporters, locations and times. Remote sensing data provide an alternative approach to monitoring crop growth over large areas in a more consistent and quantitative way. In the recent years, remote sensing data have been used to detect vegetation phenology at 1-km spatial resolution globally. However, agricultural applications at field scale require finer spatial resolution remote sensing data. Landsat (30-m) data have been successfully used for agricultural applications. There are many medium resolution sensors available today or in near future. These include Landsat, SPOT, RapidEye, ASTER and future Sentinel-2 etc. Approaches have been developed in the past several years to integrate remote sensing data from different sensors which may have different sensor characteristics, and spatial and temporal resolutions. This allows us opportunities today to map crop growth stages and conditions using dense time-series remote sensing at field scales. However, remotely sensed phenology (or phenological metrics) is normally derived based on the mathematical functions of the time-series data. The phenological metrics are determined by either identifying inflection (curvature) points or some pre-defined thresholds in the remote sensing phenology algorithms. Furthermore, physiological crop growth stages may not be directly correlated to the remotely sensed phenology. The relationship between remotely sensed phenology and crop growth stages is likely to vary for specific crop types and varieties, growing stages, conditions and even locations. In this presentation, we will examine the relationship between remotely sensed phenology and crop growth stages using in-situ measurements from Fluxnet sites and crop progress reports from USDA NASS. We will present remote sensing approaches and focus on: 1) integrating multiple sources of remote sensing data; and 2) extracting crop phenology at field scales. An example in the U.S. Corn Belt area will be presented and analyzed. Future directions for mapping crop growth stages will be discussed.

The impact of wave number selection and spin up time when using spectral nudging for dynamical downscaling applications

NASA Astrophysics Data System (ADS)

Gómez, Breogán; Miguez-Macho, Gonzalo

2017-04-01

Nudging techniques are commonly used to constrain the evolution of numerical models to a reference dataset that is typically of a lower resolution. The nudged model retains some of the features of the reference field while incorporating its own dynamics to the solution. These characteristics have made nudging very popular in dynamic downscaling applications that cover from shot range, single case studies, to multi-decadal regional climate simulations. Recently, a variation of this approach called Spectral Nudging, has gained popularity for its ability to maintain the higher temporal and spatial variability of the model results, while forcing the large scales in the solution with a coarser resolution field. In this work, we focus on a not much explored aspect of this technique: the impact of selecting different cut-off wave numbers and spin-up times. We perform four-day long simulations with the WRF model, daily for three different one-month periods that include a free run and several Spectral Nudging experiments with cut-off wave numbers ranging from the smallest to the largest possible (full Grid Nudging). Results show that Spectral Nudging is very effective at imposing the selected scales onto the solution, while allowing the limited area model to incorporate finer scale features. The model error diminishes rapidly as the nudging expands over broader parts of the spectrum, but this decreasing trend ceases sharply at cut-off wave numbers equivalent to a length scale of about 1000 km, and the error magnitude changes minimally thereafter. This scale corresponds to the Rossby Radius of deformation, separating synoptic from convective scales in the flow. When nudging above this value is applied, a shifting of the synoptic patterns can occur in the solution, yielding large model errors. However, when selecting smaller scales, the fine scale contribution of the model is damped, thus making 1000 km the appropriate scale threshold to nudge in order to balance both effects. Finally, we note that longer spin-up times are needed for model errors to stabilize when using Spectral Nudging than with Grid Nudging. Our results suggest that this time is between 36 and 48 hours.

Multiple energetic injections in a strong spike-like solar burst

NASA Technical Reports Server (NTRS)

Kaufmann, P.; Correia, E.; Costa, J. E. R.; Dennis, B. R.; Hurford, G. H.; Brown, J. C.

1983-01-01

An intense and fast spike-like solar burst was built up of short time scale structures superimposed on an underlying gradual emission, the time evolution of which shows remarkable proportionality between hard X-ray and microwave fluxes. The finer time structure were best defined at mm-microwaves. At the peak of the event, the finer structures repeat every 30x60ms. The more slowly varying component with a time scale of about 1 second was identified in microwave hard X-rays throughout the burst duration. It is suggested that X-ray fluxes might also be proportional to the repetition rate of basic units of energy injection (quasi-quantized). The relevant parameters of one primary energy release site are estimated both in the case where hard X-rays are produced primarily by thick-target bremsstrahlung, and when they are purely thermal. The relation of this figure to global energy considerations is discussed.

Influence of Complex Terrain on Wind Fields in the Mojave Desert, Southwestern US

NASA Astrophysics Data System (ADS)

Clow, G. D.; Reynolds, R. L.; Urban, F. E.; Bogle, R.; Vogel, J. M.

2009-12-01

The complex terrain of southern California has important effects on the winds in this dust-producing region. We use the Weather Research and Forecasting Model (WRF) to investigate the influences of rugged topography on the wind field in the Mojave Desert at a variety of scales. For this study, the WRF model was used in a retrospective mode over the time period 2000-to-present, with horizontal resolutions as fine as 1-km in specific areas of interest (i.e., known dust-source areas). At a regional scale, the juxtaposition of California's Central Valley with the Sierra Nevada Mountain Range often generates a band of strong winds extending eastward from the southern end of the Sierra Nevada and Tehachapi Mountains across the Mojave Desert and into Arizona. At finer scales, WRF-derived winds within this band reveal terrain deflection, focusing, channeling, and rapid direction change over short distances. These effects are important for assessing the capacity of wind to produce dust at potential dust-source areas during specific events, and for determining dust-transport pathways. Comparison of the WRF results during strong wind events with data from meteorological stations having dust emission instruments (saltation sensors and/or wind-triggered time-lapse cameras) help elucidate landscape conditions that influence dust emission and patterns of dust transport.

Spatio-temporal Granger causality: a new framework

PubMed Central

Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A.; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

2015-01-01

That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

Seafloor Mapping and Benthic Habitats off Assateague Island National Seashore: can we Resolve any Effects of Superstorm Sandy?

NASA Astrophysics Data System (ADS)

Miller, D.; Trembanis, A. C.; Kennedy, E.; Rusch, H.; Rothermel, E.

2016-02-01

The National Park Service has partnered with faculty and students at the University of Delaware to map the length of Assateague Island and sample benthic communities there for two purposes: (1) to provide a complete inventory of benthic habitats and their biota, and (2) to determine if any changes from a pre-storm survey can be ascribed to Superstorm Sandy in 2012. During the 2014 and 2015 field seasons over 75 km2 of high-resolution ( 50 cm/pixel) side-scan sonar and collocated bathymetry were collected with a surface vessel mounted bathy side-scan sonar (EdgeTech 6205), spanning the shore from depths of less than 2 m out to a distance of approximately 1 nautical mile and depths of 10-12 m. Furthermore, we have resampled using standard methodology (modified Young grab and 0.5-mm sieve) a subset of the previously sampled benthic stations that represent all sediment classes identified in prior studies. Additionally, we have obtained novel data with our ROV and AUV assets, including finer scale bottom video and multibeam bathymetry, at specifically chosen locations in order to enhance understanding of the benthic habitat and bottom type changes. In addition to providing a habitat and faunal inventory for resource management purposes, we will compare our side scan and benthic survey data to the pre-storm 2011 data products with comparable coverage. To date we have found that ArcGIS and ENVI sediment classifications agree well with those from the 2011 study, but spatially we note more areas of finer sediments and less of gravel. As was expected, 2014 benthic assemblages differ significantly among sediment classes (PRIMER ANOSIM), and sediment class is the best predictor of the benthic community (PERMANOVA+ distance-based RDA). Our goal here is to use consistent analytical approaches to characterize changes that occur over season and inter-annual time scales. This is a critical step toward attributing sediment, habitat and biological changes to Superstorm Sandy.

Improvement of sub-20nm pattern quality with dose modulation technique for NIL template production

NASA Astrophysics Data System (ADS)

Yagawa, Keisuke; Ugajin, Kunihiro; Suenaga, Machiko; Kanamitsu, Shingo; Motokawa, Takeharu; Hagihara, Kazuki; Arisawa, Yukiyasu; Kobayashi, Sachiko; Saito, Masato; Ito, Masamitsu

2016-04-01

Nanoimprint lithography (NIL) technology is in the spotlight as a next-generation semiconductor manufacturing technique for integrated circuits at 22 nm and beyond. NIL is the unmagnified lithography technique using template which is replicated from master templates. On the other hand, master templates are currently fabricated by electron-beam (EB) lithography[1]. In near future, finer patterns less than 15nm will be required on master template and EB data volume increases exponentially. So, we confront with a difficult challenge. A higher resolution EB mask writer and a high performance fabrication process will be required. In our previous study, we investigated a potential of photomask fabrication process for finer patterning and achieved 15.5nm line and space (L/S) pattern on template by using VSB (Variable Shaped Beam) type EB mask writer and chemically amplified resist. In contrast, we found that a contrast loss by backscattering decreases the performance of finer patterning. For semiconductor devices manufacturing, we must fabricate complicated patterns which includes high and low density simultaneously except for consecutive L/S pattern. Then it's quite important to develop a technique to make various size or coverage patterns all at once. In this study, a small feature pattern was experimentally formed on master template with dose modulation technique. This technique makes it possible to apply the appropriate exposure dose for each pattern size. As a result, we succeed to improve the performance of finer patterning in bright field area. These results show that the performance of current EB lithography process have a potential to fabricate NIL template.

Ghost reefs: Nautical charts document large spatial scale of coral reef loss over 240 years

PubMed Central

McClenachan, Loren; O’Connor, Grace; Neal, Benjamin P.; Pandolfi, John M.; Jackson, Jeremy B. C.

2017-01-01

Massive declines in population abundances of marine animals have been documented over century-long time scales. However, analogous loss of spatial extent of habitat-forming organisms is less well known because georeferenced data are rare over long time scales, particularly in subtidal, tropical marine regions. We use high-resolution historical nautical charts to quantify changes to benthic structure over 240 years in the Florida Keys, finding an overall loss of 52% (SE, 6.4%) of the area of the seafloor occupied by corals. We find a strong spatial dimension to this decline; the spatial extent of coral in Florida Bay and nearshore declined by 87.5% (SE, 7.2%) and 68.8% (SE, 7.5%), respectively, whereas that of offshore areas of coral remained largely intact. These estimates add to finer-scale loss in live coral cover exceeding 90% in some locations in recent decades. The near-complete elimination of the spatial coverage of nearshore coral represents an underappreciated spatial component of the shifting baseline syndrome, with important lessons for other species and ecosystems. That is, modern surveys are typically designed to assess change only within the species’ known, extant range. For species ranging from corals to sea turtles, this approach may overlook spatial loss over longer time frames, resulting in both overly optimistic views of their current conservation status and underestimates of their restoration potential. PMID:28913420

Potential Technologies for Assessing Risk Associated with a Mesoscale Forecast

DTIC Science & Technology

2015-10-01

American GFS models, and informally applied on the Weather Research and Forecasting ( WRF ) model. The current CI equation is as follows...Reen B, Penc R. Investigating surface bias errors in the Weather Research and Forecasting ( WRF ) model using a Geographic Information System (GIS). J...Forecast model ( WRF -ARW) with extensions that might include finer terrain resolutions and more detailed representations of the underlying atmospheric

Computed Tomography Status

DOE R&D Accomplishments Database

Hansche, B. D.

1983-01-01

Computed tomography (CT) is a relatively new radiographic technique which has become widely used in the medical field, where it is better known as computerized axial tomographic (CAT) scanning. This technique is also being adopted by the industrial radiographic community, although the greater range of densities, variation in samples sizes, plus possible requirement for finer resolution make it difficult to duplicate the excellent results that the medical scanners have achieved.

Solar-induced chlorophyll fluorescence is strongly correlated with terrestrial photosynthesis for a wide variety of biomes: First global analysis based on OCO-2 and flux tower observations.

PubMed

Li, Xing; Xiao, Jingfeng; He, Binbin; Arain, M Altaf; Beringer, Jason; Desai, Ankur R; Emmel, Carmen; Hollinger, David Y; Krasnova, Alisa; Mammarella, Ivan; Noe, Steffen M; Serrano Ortiz, Penélope; Rey-Sanchez, Camilo; Rocha, Adrian V; Varlagin, Andrej

2018-05-07

Solar-induced chlorophyll fluorescence (SIF) has been increasingly used as a proxy for terrestrial gross primary productivity (GPP). Previous work mainly evaluated the relationship between satellite-observed SIF and gridded GPP products both based on coarse spatial resolutions. Finer-resolution SIF (1.3 km × 2.25 km) measured from the Orbiting Carbon Observatory-2 (OCO-2) provides the first opportunity to examine the SIF-GPP relationship at the ecosystem scale using flux tower GPP data. However, it remains unclear how strong the relationship is for each biome and whether a robust, universal relationship exists across a variety of biomes. Here we conducted the first global analysis of the relationship between OCO-2 SIF and tower GPP for a total of 64 flux sites across the globe encompassing eight major biomes. OCO-2 SIF showed strong correlations with tower GPP at both mid-day and daily timescales, with the strongest relationship observed for daily SIF at the 757 nm (R 2 =0.72, p<0.0001). Strong linear relationships between SIF and GPP were consistently found for all biomes (R 2 =0.57-0.79, p<0.0001) except for evergreen broadleaf forests (R 2 =0.16, p<0.05) at the daily timescale. A higher slope was found for C 4 grasslands and croplands than for C 3 ecosystems. The generally consistent slope of the relationship among biomes suggests a nearly universal rather than biome-specific SIF-GPP relationship, and this finding is an important distinction and simplification compared to previous results. OCO-2 SIF generally had a better performance for predicting GPP than satellite-derived vegetation indices and a light use efficiency model. The universal SIF-GPP relationship can potentially lead to more accurate GPP estimates regionally or globally. Our findings revealed the remarkable ability of finer-resolution SIF observations from OCO-2 and other new or future missions (e.g., TROPOMI, FLEX) for estimating terrestrial photosynthesis across a wide variety of biomes and identified their potential and limitations for ecosystem functioning and carbon cycle studies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Estimating Top-of-Atmosphere Thermal Infrared Radiance Using MERRA-2 Atmospheric Data

NASA Astrophysics Data System (ADS)

Kleynhans, Tania

Space borne thermal infrared sensors have been extensively used for environmental research as well as cross-calibration of other thermal sensing systems. Thermal infrared data from satellites such as Landsat and Terra/MODIS have limited temporal resolution (with a repeat cycle of 1 to 2 days for Terra/MODIS, and 16 days for Landsat). Thermal instruments with finer temporal resolution on geostationary satellites have limited utility for cross-calibration due to their large view angles. Reanalysis atmospheric data is available on a global spatial grid at three hour intervals making it a potential alternative to existing satellite image data. This research explores using the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data product to predict top-of-atmosphere (TOA) thermal infrared radiance globally at time scales finer than available satellite data. The MERRA-2 data product provides global atmospheric data every three hours from 1980 to the present. Due to the high temporal resolution of the MERRA-2 data product, opportunities for novel research and applications are presented. While MERRA-2 has been used in renewable energy and hydrological studies, this work seeks to leverage the model to predict TOA thermal radiance. Two approaches have been followed, namely physics-based approach and a supervised learning approach, using Terra/MODIS band 31 thermal infrared data as reference. The first physics-based model uses forward modeling to predict TOA thermal radiance. The second model infers the presence of clouds from the MERRA-2 atmospheric data, before applying an atmospheric radiative transfer model. The last physics-based model parameterized the previous model to minimize computation time. The second approach applied four different supervised learning algorithms to the atmospheric data. The algorithms included a linear least squares regression model, a non-linear support vector regression (SVR) model, a multi-layer perceptron (MLP), and a convolutional neural network (CNN). This research found that the multi-layer perceptron model produced the lowest error rates overall, with an RMSE of 1.22W / m2 sr mum when compared to actual Terra/MODIS band 31 image data. This research further aimed to characterize the errors associated with each method so that any potential user will have the best information available should they wish to apply these methods towards their own application.

MODFLOW-LGR: Practical application to a large regional dataset

NASA Astrophysics Data System (ADS)

Barnes, D.; Coulibaly, K. M.

2011-12-01

In many areas of the US, including southwest Florida, large regional-scale groundwater models have been developed to aid in decision making and water resources management. These models are subsequently used as a basis for site-specific investigations. Because the large scale of these regional models is not appropriate for local application, refinement is necessary to analyze the local effects of pumping wells and groundwater related projects at specific sites. The most commonly used approach to date is Telescopic Mesh Refinement or TMR. It allows the extraction of a subset of the large regional model with boundary conditions derived from the regional model results. The extracted model is then updated and refined for local use using a variable sized grid focused on the area of interest. MODFLOW-LGR, local grid refinement, is an alternative approach which allows model discretization at a finer resolution in areas of interest and provides coupling between the larger "parent" model and the locally refined "child." In the present work, these two approaches are tested on a mining impact assessment case in southwest Florida using a large regional dataset (The Lower West Coast Surficial Aquifer System Model). Various metrics for performance are considered. They include: computation time, water balance (as compared to the variable sized grid), calibration, implementation effort, and application advantages and limitations. The results indicate that MODFLOW-LGR is a useful tool to improve local resolution of regional scale models. While performance metrics, such as computation time, are case-dependent (model size, refinement level, stresses involved), implementation effort, particularly when regional models of suitable scale are available, can be minimized. The creation of multiple child models within a larger scale parent model makes it possible to reuse the same calibrated regional dataset with minimal modification. In cases similar to the Lower West Coast model, where a model is larger than optimal for direct application as a parent grid, a combination of TMR and LGR approaches should be used to develop a suitable parent grid.

Validation and application of MODIS-derived clean snow albedo and dust radiative forcing

NASA Astrophysics Data System (ADS)

Rittger, K. E.; Bryant, A. C.; Seidel, F. C.; Bair, E. H.; Skiles, M.; Goodale, C. E.; Ramirez, P.; Mattmann, C. A.; Dozier, J.; Painter, T.

2012-12-01

Snow albedo is an important control on snowmelt. Though albedo evolution of aging snow can be roughly modeled from grain growth, dust and other light absorbing impurities are extrinsic and therefore must be measured. Estimates of clean snow albedo and surface radiative forcing from impurities, which can be inferred from MODIS 500 m surface reflectance products, can provide this driving data for snowmelt models. Here we use MODSCAG (MODIS snow covered area and grain size) to estimate the clean snow albedo and MODDRFS (MODIS dust radiative forcing of snow) to estimate the additional absorbed solar radiation from dust and black carbon. With its finer spatial (20 m) and spectral (10 nm) resolutions, AVIRIS provides a way to estimate the accuracy of MODIS products and understand variability of snow albedo at a finer scale that we explore though a range of topography. The AVIRIS database includes images from late in the accumulation season through the melt season when we are most interested in changes in snow albedo. In addition to the spatial validation, we employ the best estimate of albedo from MODIS in an energy balance reconstruction model to estimate the maximum snow water equivalent. MODDRFS calculates radiative forcing only in pixels that are completely snow-covered, so we spatially interpolate the product to estimate the forcing in all pixels where MODSCAG has given us estimates of clean snow albedo. Comparisons with snow pillows and courses show better agreement when the radiative forcing from absorbing impurities is included in the energy balance reconstruction.

Aiding alternatives assessment with an uncertainty-tolerant hazard scoring method.

PubMed

Faludi, Jeremy; Hoang, Tina; Gorman, Patrick; Mulvihill, Martin

2016-11-01

This research developed a single-score system to simplify and clarify decision-making in chemical alternatives assessment, accounting for uncertainty. Today, assessing alternatives to hazardous constituent chemicals is a difficult task-rather than comparing alternatives by a single definitive score, many independent toxicological variables must be considered at once, and data gaps are rampant. Thus, most hazard assessments are only comprehensible to toxicologists, but business leaders and politicians need simple scores to make decisions. In addition, they must balance hazard against other considerations, such as product functionality, and they must be aware of the high degrees of uncertainty in chemical hazard data. This research proposes a transparent, reproducible method to translate eighteen hazard endpoints into a simple numeric score with quantified uncertainty, alongside a similar product functionality score, to aid decisions between alternative products. The scoring method uses Clean Production Action's GreenScreen as a guide, but with a different method of score aggregation. It provides finer differentiation between scores than GreenScreen's four-point scale, and it displays uncertainty quantitatively in the final score. Displaying uncertainty also illustrates which alternatives are early in product development versus well-defined commercial products. This paper tested the proposed assessment method through a case study in the building industry, assessing alternatives to spray polyurethane foam insulation containing methylene diphenyl diisocyanate (MDI). The new hazard scoring method successfully identified trade-offs between different alternatives, showing finer resolution than GreenScreen Benchmarking. Sensitivity analysis showed that different weighting schemes in hazard scores had almost no effect on alternatives ranking, compared to uncertainty from data gaps. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spotlight-Mode Synthetic Aperture Radar Processing for High-Resolution Lunar Mapping

NASA Technical Reports Server (NTRS)

Harcke, Leif; Weintraub, Lawrence; Yun, Sang-Ho; Dickinson, Richard; Gurrola, Eric; Hensley, Scott; Marechal, Nicholas

2010-01-01

During the 2008-2009 year, the Goldstone Solar System Radar was upgraded to support radar mapping of the lunar poles at 4 m resolution. The finer resolution of the new system and the accompanying migration through resolution cells called for spotlight, rather than delay-Doppler, imaging techniques. A new pre-processing system supports fast-time Doppler removal and motion compensation to a point. Two spotlight imaging techniques which compensate for phase errors due to i) out of focus-plane motion of the radar and ii) local topography, have been implemented and tested. One is based on the polar format algorithm followed by a unique autofocus technique, the other is a full bistatic time-domain backprojection technique. The processing system yields imagery of the specified resolution. Products enabled by this new system include topographic mapping through radar interferometry, and change detection techniques (amplitude and coherent change) for geolocation of the NASA LCROSS mission impact site.

Structure-level fuel load assessment in the wildland-urban interface: a fusion of airborne laser scanning and spectral remote-sensing methodologies

Treesearch

Nicholas S. Skowronski; Scott Haag; Jim Trimble; Kenneth L. Clark; Michael R. Gallagher; Richard G. Lathrop

2015-01-01

Large-scale fuel assessments are useful for developing policy aimed at mitigating wildfires in the wildland-urban interface (WUI), while finer-scale characterisation is necessary for maximising the effectiveness of fuel reduction treatments and directing suppression activities. We developed and tested an objective, consistent approach for characterising hazardous fuels...

NEIGHBORHOOD SCALE AIR QUALITY MODELING IN HOUSTON USING URBAN CANOPY PARAMETERS IN MM5 AND CMAQ WITH IMPROVED CHARACTERIZATION OF MESOSCALE LAKE-LAND BREEZE CIRCULATION

EPA Science Inventory

Advanced capability of air quality simulation models towards accurate performance at finer scales will be needed for such models to serve as tools for performing exposure and risk assessments in urban areas. It is recognized that the impact of urban features such as street and t...

Temporal carbon dynamics of forests in Washington, US: implications for ecological theory and carbon management

Treesearch

Crystal L. Raymond; Donald McKenzie

2014-01-01

We quantified carbon (C) dynamics of forests in Washington, US using theoretical models of C dynamics as a function of forest age. We fit empirical models to chronosequences of forest inventory data at two scales: a coarse-scale ecosystem classification (ecosections) and forest types (potential vegetation) within ecosections. We hypothesized that analysis at the finer...

Quantum interpolation for high-resolution sensing

PubMed Central

Ajoy, Ashok; Liu, Yi-Xiang; Saha, Kasturi; Marseglia, Luca; Jaskula, Jean-Christophe; Bissbort, Ulf; Cappellaro, Paola

2017-01-01

Recent advances in engineering and control of nanoscale quantum sensors have opened new paradigms in precision metrology. Unfortunately, hardware restrictions often limit the sensor performance. In nanoscale magnetic resonance probes, for instance, finite sampling times greatly limit the achievable sensitivity and spectral resolution. Here we introduce a technique for coherent quantum interpolation that can overcome these problems. Using a quantum sensor associated with the nitrogen vacancy center in diamond, we experimentally demonstrate that quantum interpolation can achieve spectroscopy of classical magnetic fields and individual quantum spins with orders of magnitude finer frequency resolution than conventionally possible. Not only is quantum interpolation an enabling technique to extract structural and chemical information from single biomolecules, but it can be directly applied to other quantum systems for superresolution quantum spectroscopy. PMID:28196889

Quantum interpolation for high-resolution sensing.

PubMed

Ajoy, Ashok; Liu, Yi-Xiang; Saha, Kasturi; Marseglia, Luca; Jaskula, Jean-Christophe; Bissbort, Ulf; Cappellaro, Paola

2017-02-28

Recent advances in engineering and control of nanoscale quantum sensors have opened new paradigms in precision metrology. Unfortunately, hardware restrictions often limit the sensor performance. In nanoscale magnetic resonance probes, for instance, finite sampling times greatly limit the achievable sensitivity and spectral resolution. Here we introduce a technique for coherent quantum interpolation that can overcome these problems. Using a quantum sensor associated with the nitrogen vacancy center in diamond, we experimentally demonstrate that quantum interpolation can achieve spectroscopy of classical magnetic fields and individual quantum spins with orders of magnitude finer frequency resolution than conventionally possible. Not only is quantum interpolation an enabling technique to extract structural and chemical information from single biomolecules, but it can be directly applied to other quantum systems for superresolution quantum spectroscopy.

Propagation-based phase-contrast tomography for high-resolution lung imaging with laboratory sources

NASA Astrophysics Data System (ADS)

Krenkel, Martin; Töpperwien, Mareike; Dullin, Christian; Alves, Frauke; Salditt, Tim

2016-03-01

We have performed high-resolution phase-contrast tomography on whole mice with a laboratory setup. Enabled by a high-brilliance liquid-metal-jet source, we show the feasibility of propagation-based phase contrast in local tomography even in the presence of strongly absorbing surrounding tissue as it is the case in small animal imaging of the lung. We demonstrate the technique by reconstructions of the mouse lung for two different fields of view, covering the whole organ, and a zoom to the local finer structure of terminal airways and alveoli. With a resolution of a few micrometers and the wide availability of the technique, studies of larger biological samples at the cellular level become possible.

Enhancing GIS Capabilities for High Resolution Earth Science Grids

NASA Astrophysics Data System (ADS)

Koziol, B. W.; Oehmke, R.; Li, P.; O'Kuinghttons, R.; Theurich, G.; DeLuca, C.

2017-12-01

Applications for high performance GIS will continue to increase as Earth system models pursue more realistic representations of Earth system processes. Finer spatial resolution model input and output, unstructured or irregular modeling grids, data assimilation, and regional coordinate systems present novel challenges for GIS frameworks operating in the Earth system modeling domain. This presentation provides an overview of two GIS-driven applications that combine high performance software with big geospatial datasets to produce value-added tools for the modeling and geoscientific community. First, a large-scale interpolation experiment using National Hydrography Dataset (NHD) catchments, a high resolution rectilinear CONUS grid, and the Earth System Modeling Framework's (ESMF) conservative interpolation capability will be described. ESMF is a parallel, high-performance software toolkit that provides capabilities (e.g. interpolation) for building and coupling Earth science applications. ESMF is developed primarily by the NOAA Environmental Software Infrastructure and Interoperability (NESII) group. The purpose of this experiment was to test and demonstrate the utility of high performance scientific software in traditional GIS domains. Special attention will be paid to the nuanced requirements for dealing with high resolution, unstructured grids in scientific data formats. Second, a chunked interpolation application using ESMF and OpenClimateGIS (OCGIS) will demonstrate how spatial subsetting can virtually remove computing resource ceilings for very high spatial resolution interpolation operations. OCGIS is a NESII-developed Python software package designed for the geospatial manipulation of high-dimensional scientific datasets. An overview of the data processing workflow, why a chunked approach is required, and how the application could be adapted to meet operational requirements will be discussed here. In addition, we'll provide a general overview of OCGIS's parallel subsetting capabilities including challenges in the design and implementation of a scientific data subsetter.

High Quality Data for Grid Integration Studies

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

Clifton, Andrew; Draxl, Caroline; Sengupta, Manajit

As variable renewable power penetration levels increase in power systems worldwide, renewable integration studies are crucial to ensure continued economic and reliable operation of the power grid. The existing electric grid infrastructure in the US in particular poses significant limitations on wind power expansion. In this presentation we will shed light on requirements for grid integration studies as far as wind and solar energy are concerned. Because wind and solar plants are strongly impacted by weather, high-resolution and high-quality weather data are required to drive power system simulations. Future data sets will have to push limits of numerical weather predictionmore » to yield these high-resolution data sets, and wind data will have to be time-synchronized with solar data. Current wind and solar integration data sets are presented. The Wind Integration National Dataset (WIND) Toolkit is the largest and most complete grid integration data set publicly available to date. A meteorological data set, wind power production time series, and simulated forecasts created using the Weather Research and Forecasting Model run on a 2-km grid over the continental United States at a 5-min resolution is now publicly available for more than 126,000 land-based and offshore wind power production sites. The National Solar Radiation Database (NSRDB) is a similar high temporal- and spatial resolution database of 18 years of solar resource data for North America and India. The need for high-resolution weather data pushes modeling towards finer scales and closer synchronization. We also present how we anticipate such datasets developing in the future, their benefits, and the challenges with using and disseminating such large amounts of data.« less

Genome-wide SNPs reveal the drivers of gene flow in an urban population of the Asian Tiger Mosquito, Aedes albopictus.

PubMed

Schmidt, Thomas L; Rašić, Gordana; Zhang, Dongjing; Zheng, Xiaoying; Xi, Zhiyong; Hoffmann, Ary A

2017-10-01

Aedes albopictus is a highly invasive disease vector with an expanding worldwide distribution. Genetic assays using low to medium resolution markers have found little evidence of spatial genetic structure even at broad geographic scales, suggesting frequent passive movement along human transportation networks. Here we analysed genetic structure of Aedes albopictus collected from 12 sample sites in Guangzhou, China, using thousands of genome-wide single nucleotide polymorphisms (SNPs). We found evidence for passive gene flow, with distance from shipping terminals being the strongest predictor of genetic distance among mosquitoes. As further evidence of passive dispersal, we found multiple pairs of full-siblings distributed between two sample sites 3.7 km apart. After accounting for geographical variability, we also found evidence for isolation by distance, previously undetectable in Ae. albopictus. These findings demonstrate how large SNP datasets and spatially-explicit hypothesis testing can be used to decipher processes at finer geographic scales than formerly possible. Our approach can be used to help predict new invasion pathways of Ae. albopictus and to refine strategies for vector control that involve the transformation or suppression of mosquito populations.

Maintaining a Local Data Integration System in Support of Weather Forecast Operations

NASA Technical Reports Server (NTRS)

Watson, Leela R.; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian

2010-01-01

Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) at Johnson Space Center in Houston, TX have used a local data integration system (LDIS) as part of their forecast and warning operations. The original LDIS was developed by NASA's Applied Meteorology Unit (AMU; Bauman et ai, 2004) in 1998 (Manobianco and Case 1998) and has undergone subsequent improvements. Each has benefited from three-dimensional (3-D) analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national- or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive understanding of evolving fine-scale weather features

Remote sensing of soil moisture using airborne hyperspectral data

USGS Publications Warehouse

Finn, M.; Lewis, M.; Bosch, D.; Giraldo, Mario; Yamamoto, K.; Sullivan, D.; Kincaid, R.; Luna, R.; Allam, G.; Kvien, Craig; Williams, M.

2011-01-01

Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

Remote sensing of soil moisture using airborne hyperspectral data

USGS Publications Warehouse

Finn, Michael P.; Lewis, Mark (David); Bosch, David D.; Giraldo, Mario; Yamamoto, Kristina H.; Sullivan, Dana G.; Kincaid, Russell; Luna, Ronaldo; Allam, Gopala Krishna; Kvien, Craig; Williams, Michael S.

2011-01-01

Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R 2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

Examination of turbulent entrainment-mixing mechanisms using a combined approach

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

Lu, C.; Liu, Y.; Niu, S.

2011-10-01

Turbulent entrainment-mixing mechanisms are investigated by applying a combined approach to the aircraft measurements of three drizzling and two nondrizzling stratocumulus clouds collected over the U.S. Department of Energy's Atmospheric Radiation Measurement Southern Great Plains site during the March 2000 cloud Intensive Observation Period. Microphysical analysis shows that the inhomogeneous entrainment-mixing process occurs much more frequently than the homogeneous counterpart, and most cases of the inhomogeneous entrainment-mixing process are close to the extreme scenario, having drastically varying cloud droplet concentration but roughly constant volume-mean radius. It is also found that the inhomogeneous entrainment-mixing process can occur both near the cloudmore » top and in the middle level of a cloud, and in both the nondrizzling clouds and nondrizzling legs in the drizzling clouds. A new dimensionless number, the scale number, is introduced as a dynamical measure for different entrainment-mixing processes, with a larger scale number corresponding to a higher degree of homogeneous entrainment mixing. Further empirical analysis shows that the scale number that separates the homogeneous from the inhomogeneous entrainment-mixing process is around 50, and most legs have smaller scale numbers. Thermodynamic analysis shows that sampling average of filament structures finer than the instrumental spatial resolution also contributes to the dominance of inhomogeneous entrainment-mixing mechanism. The combined microphysical-dynamical-thermodynamic analysis sheds new light on developing parameterization of entrainment-mixing processes and their microphysical and radiative effects in large-scale models.« less

Simulation of all-scale atmospheric dynamics on unstructured meshes

NASA Astrophysics Data System (ADS)

Smolarkiewicz, Piotr K.; Szmelter, Joanna; Xiao, Feng

2016-10-01

The advance of massively parallel computing in the nineteen nineties and beyond encouraged finer grid intervals in numerical weather-prediction models. This has improved resolution of weather systems and enhanced the accuracy of forecasts, while setting the trend for development of unified all-scale atmospheric models. This paper first outlines the historical background to a wide range of numerical methods advanced in the process. Next, the trend is illustrated with a technical review of a versatile nonoscillatory forward-in-time finite-volume (NFTFV) approach, proven effective in simulations of atmospheric flows from small-scale dynamics to global circulations and climate. The outlined approach exploits the synergy of two specific ingredients: the MPDATA methods for the simulation of fluid flows based on the sign-preserving properties of upstream differencing; and the flexible finite-volume median-dual unstructured-mesh discretisation of the spatial differential operators comprising PDEs of atmospheric dynamics. The paper consolidates the concepts leading to a family of generalised nonhydrostatic NFTFV flow solvers that include soundproof PDEs of incompressible Boussinesq, anelastic and pseudo-incompressible systems, common in large-eddy simulation of small- and meso-scale dynamics, as well as all-scale compressible Euler equations. Such a framework naturally extends predictive skills of large-eddy simulation to the global atmosphere, providing a bottom-up alternative to the reverse approach pursued in the weather-prediction models. Theoretical considerations are substantiated by calculations attesting to the versatility and efficacy of the NFTFV approach. Some prospective developments are also discussed.

Examining Extreme Events Using Dynamically Downscaled 12-km WRF Simulations

EPA Science Inventory

Continued improvements in the speed and availability of computational resources have allowed dynamical downscaling of global climate model (GCM) projections to be conducted at increasingly finer grid scales and over extended time periods. The implementation of dynamical downscal...

Aggregating pixel-level basal area predictions derived from LiDAR data to industrial forest stands in North-Central Idaho

Treesearch

Andrew T. Hudak; Jeffrey S. Evans; Nicholas L. Crookston; Michael J. Falkowski; Brant K. Steigers; Rob Taylor; Halli Hemingway

2008-01-01

Stand exams are the principal means by which timber companies monitor and manage their forested lands. Airborne LiDAR surveys sample forest stands at much finer spatial resolution and broader spatial extent than is practical on the ground. In this paper, we developed models that leverage spatially intensive and extensive LiDAR data and a stratified random sample of...

Designing an Error Resolution Checklist for a Shared Manned-Unmanned Environment

DTIC Science & Technology

2010-06-01

performance during the Olympics. Thank you to Birsen Donmez, who took an active role in my statistics instruction. I appreciate your time and patience...in teaching me the finer details of “varsity statistics ”. Also, thank you for being so responsive through e-mail, even though you are now located in...105! 6.3.! Experiment recommendations and future work................................................ 105! Appendix A: Descriptive Statistics

A Multiscale Surface Water Temperature Data Acquisition Platform: Tests on Lake Geneva, Switzerland

NASA Astrophysics Data System (ADS)

Barry, D. A.; Irani Rahaghi, A.; Lemmin, U.; Riffler, M.; Wunderle, S.

2015-12-01

An improved understanding of surface transport processes is necessary to predict sediment, pollutant and phytoplankton patterns in large lakes. Lake surface water temperature (LSWT), which varies in space and time, reflects meteorological and climatological forcing more than any other physical lake parameter. There are different data sources for LSWT mapping, including remote sensing and in situ measurements. Satellite data can be suitable for detecting large-scale thermal patterns, but not meso- or small scale processes. Lake surface thermography, investigated in this study, has finer resolution compared to satellite images. Thermography at the meso-scale provides the ability to ground-truth satellite imagery over scales of one to several satellite image pixels. On the other hand, thermography data can be used as a control in schemes to upscale local measurements that account for surface energy fluxes and the vertical energy budget. Independently, since such data can be collected at high frequency, they can be also useful in capturing changes in the surface signatures of meso-scale eddies and thus to quantify mixing processes. In the present study, we report results from a Balloon Launched Imaging and Monitoring Platform (BLIMP), which was developed in order to measure the LSWT at meso-scale. The BLIMP consists of a small balloon that is tethered to a boat and equipped with thermal and RGB cameras, as well as other instrumentation for location and communication. Several deployments were carried out on Lake Geneva. In a typical deployment, the BLIMP is towed by a boat, and collects high frequency data from different heights (i.e., spatial resolutions) and locations. Simultaneous ground-truthing of the BLIMP data is achieved using an autonomous craft that collects a variety of data, including in situ surface/near surface temperatures, radiation and meteorological data in the area covered by the BLIMP images. With suitable scaling, our results show good consistency between in situ, BLIMP and concurrent satellite data. In addition, the BLIMP thermography reveals (hydrodynamically-driven) structures in the LSWT - an obvious example being mixing of river discharges.

Delineating Biophysical Environments of the Sunda Banda Seascape, Indonesia

PubMed Central

Wang, Mingshu; Ahmadia, Gabby N.; Chollett, Iliana; Huang, Charles; Fox, Helen; Wijonarno, Anton; Madden, Marguerite

2015-01-01

The Sunda Banda Seascape (SBS), located in the center of the Coral Triangle, is a global center of marine biodiversity and a conservation priority. We proposed the first biophysical environmental delineation of the SBS using globally available satellite remote sensing and model-assimilated data to categorize this area into unique and meaningful biophysical classes. Specifically, the SBS was partitioned into eight biophysical classes characterized by similar sea surface temperature, chlorophyll a concentration, currents, and salinity patterns. Areas within each class were expected to have similar habitat types and ecosystem functions. Our work supplemented prevailing global marine management schemes by focusing in on a regional scale with finer spatial resolution. It also provided a baseline for academic research, ecological assessments and will facilitate marine spatial planning and conservation activities in the area. In addition, the framework and methods of delineating biophysical environments we presented can be expanded throughout the whole Coral Triangle to support research and conservation activities in this important region. PMID:25648170

A simple autocorrelation algorithm for determining grain size from digital images of sediment

USGS Publications Warehouse

Rubin, D.M.

2004-01-01

Autocorrelation between pixels in digital images of sediment can be used to measure average grain size of sediment on the bed, grain-size distribution of bed sediment, and vertical profiles in grain size in a cross-sectional image through a bed. The technique is less sensitive than traditional laboratory analyses to tails of a grain-size distribution, but it offers substantial other advantages: it is 100 times as fast; it is ideal for sampling surficial sediment (the part that interacts with a flow); it can determine vertical profiles in grain size on a scale finer than can be sampled physically; and it can be used in the field to provide almost real-time grain-size analysis. The technique can be applied to digital images obtained using any source with sufficient resolution, including digital cameras, digital video, or underwater digital microscopes (for real-time grain-size mapping of the bed). ?? 2004, SEPM (Society for Sedimentary Geology).

The importance of structural softening for the evolution and architecture of passive margins

PubMed Central

Duretz, T.; Petri, B.; Mohn, G.; Schmalholz, S. M.; Schenker, F. L.; Müntener, O.

2016-01-01

Lithospheric extension can generate passive margins that bound oceans worldwide. Detailed geological and geophysical studies in present and fossil passive margins have highlighted the complexity of their architecture and their multi-stage deformation history. Previous modeling studies have shown the significant impact of coarse mechanical layering of the lithosphere (2 to 4 layer crust and mantle) on passive margin formation. We built upon these studies and design high-resolution (~100–300 m) thermo-mechanical numerical models that incorporate finer mechanical layering (kilometer scale) mimicking tectonically inherited heterogeneities. During lithospheric extension a variety of extensional structures arises naturally due to (1) structural softening caused by necking of mechanically strong layers and (2) the establishment of a network of weak layers across the deforming multi-layered lithosphere. We argue that structural softening in a multi-layered lithosphere is the main cause for the observed multi-stage evolution and architecture of magma-poor passive margins. PMID:27929057

Selecting habitat to survive: the impact of road density on survival in a large carnivore.

PubMed

Basille, Mathieu; Van Moorter, Bram; Herfindal, Ivar; Martin, Jodie; Linnell, John D C; Odden, John; Andersen, Reidar; Gaillard, Jean-Michel

2013-01-01

Habitat selection studies generally assume that animals select habitat and food resources at multiple scales to maximise their fitness. However, animals sometimes prefer habitats of apparently low quality, especially when considering the costs associated with spatially heterogeneous human disturbance. We used spatial variation in human disturbance, and its consequences on lynx survival, a direct fitness component, to test the Hierarchical Habitat Selection hypothesis from a population of Eurasian lynx Lynx lynx in southern Norway. Data from 46 lynx monitored with telemetry indicated that a high proportion of forest strongly reduced the risk of mortality from legal hunting at the home range scale, while increasing road density strongly increased such risk at the finer scale within the home range. We found hierarchical effects of the impact of human disturbance, with a higher road density at a large scale reinforcing its negative impact at a fine scale. Conversely, we demonstrated that lynx shifted their habitat selection to avoid areas with the highest road densities within their home ranges, thus supporting a compensatory mechanism at fine scale enabling lynx to mitigate the impact of large-scale disturbance. Human impact, positively associated with high road accessibility, was thus a stronger driver of lynx space use at a finer scale, with home range characteristics nevertheless constraining habitat selection. Our study demonstrates the truly hierarchical nature of habitat selection, which aims at maximising fitness by selecting against limiting factors at multiple spatial scales, and indicates that scale-specific heterogeneity of the environment is driving individual spatial behaviour, by means of trade-offs across spatial scales.

Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

NASA Astrophysics Data System (ADS)

Wu, Qiusheng; Lane, Charles R.

2017-07-01

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling-spilling-merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.

Applying pollen DNA metabarcoding to the study of plant–pollinator interactions1

PubMed Central

Bell, Karen L.; Fowler, Julie; Burgess, Kevin S.; Dobbs, Emily K.; Gruenewald, David; Lawley, Brice; Morozumi, Connor; Brosi, Berry J.

2017-01-01

Premise of the study: To study pollination networks in a changing environment, we need accurate, high-throughput methods. Previous studies have shown that more highly resolved networks can be constructed by studying pollen loads taken from bees, relative to field observations. DNA metabarcoding potentially allows for faster and finer-scale taxonomic resolution of pollen compared to traditional approaches (e.g., light microscopy), but has not been applied to pollination networks. Methods: We sampled pollen from 38 bee species collected in Florida from sites differing in forest management. We isolated DNA from pollen mixtures and sequenced rbcL and ITS2 gene regions from all mixtures in a single run on the Illumina MiSeq platform. We identified species from sequence data using comprehensive rbcL and ITS2 databases. Results: We successfully built a proof-of-concept quantitative pollination network using pollen metabarcoding. Discussion: Our work underscores that pollen metabarcoding is not quantitative but that quantitative networks can be constructed based on the number of interacting individuals. Due to the frequency of contamination and false positive reads, isolation and PCR negative controls should be used in every reaction. DNA metabarcoding has advantages in efficiency and resolution over microscopic identification of pollen, and we expect that it will have broad utility for future studies of plant–pollinator interactions. PMID:28690929

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

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.

Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data

PubMed Central

Stevens, Forrest R.; Gaughan, Andrea E.; Linard, Catherine; Tatem, Andrew J.

2015-01-01

High resolution, contemporary data on human population distributions are vital for measuring impacts of population growth, monitoring human-environment interactions and for planning and policy development. Many methods are used to disaggregate census data and predict population densities for finer scale, gridded population data sets. We present a new semi-automated dasymetric modeling approach that incorporates detailed census and ancillary data in a flexible, “Random Forest” estimation technique. We outline the combination of widely available, remotely-sensed and geospatial data that contribute to the modeled dasymetric weights and then use the Random Forest model to generate a gridded prediction of population density at ~100 m spatial resolution. This prediction layer is then used as the weighting surface to perform dasymetric redistribution of the census counts at a country level. As a case study we compare the new algorithm and its products for three countries (Vietnam, Cambodia, and Kenya) with other common gridded population data production methodologies. We discuss the advantages of the new method and increases over the accuracy and flexibility of those previous approaches. Finally, we outline how this algorithm will be extended to provide freely-available gridded population data sets for Africa, Asia and Latin America. PMID:25689585

Use of UAVs for Remote Measurement of Vegetation Canopy Variables

NASA Astrophysics Data System (ADS)

Rango, A.; Laliberte, A.; Herrick, J.; Steele, C.; Bestelmeyer, B.; Chopping, M. J.

2006-12-01

Remote sensing with different sensors has proven useful for measuring vegetation canopy variables at scales ranging from landscapes down to individual plants. For use at landscape scales, such as desert grasslands invaded by shrubs, it is possible to use multi-angle imagery from satellite sensors, such as MISR and CHRIS/Proba, with geometric optical models to retrieve fractional woody plant cover. Vegetation community states can be mapped using visible and near infrared ASTER imagery at 15 m resolution. At finer scales, QuickBird satellite imagery with approximately 60 cm resolution and piloted aircraft photography with 25-80 cm resolution can be used to measure shrubs above a critical size. Tests conducted with the QuickBird data in the Jornada basin of southern New Mexico have shown that 87% of all shrubs greater than 2 m2 were detected whereas only about 29% of all shrubs less than 2 m2 were detected, even at these high resolutions. Because there is an observational gap between satellite/aircraft measurements and ground observations, we have experimented with Unmanned Aerial Vehicles (UAVs) producing digital photography with approximately 5 cm resolution. We were able to detect all shrubs greater than 2 m2, and we were able to map small subshrubs indicative of rangeland deterioration, as well as remnant grass patches, for the first time. None of these could be identified on the 60 cm resolution data. Additionally, we were able to measure canopy gaps, shrub patterns, percent bare soil, and vegetation cover over mixed rangeland vegetation. This approach is directly applicable to rangeland health monitoring, and it provides a quantitative way to assess shrub invasion over time and to detect the depletion or recovery of grass patches. Further, if the UAV images have sufficient overlap, it may be possible to exploit the stereo viewing capabilities to develop a digital elevation model from the orthophotos, with a potential for extracting canopy height. We envision two parallel routes for investigation: one which emphasizes utilization of the most technically advanced passive and active space and aircraft sensors (e.g., LIDAR, radar, Hyperion, ASTER, QuickBird follow-on) for modeling research, and a second which emphasizes minimization of costs and maximization of simplicity for monitoring purposes utilizing inexpensive sensors such as digital cameras on UAVs for arid and semiarid rangelands. The use of UAVs will provide management agencies a way to assess various vegetation canopy variables for a very reasonable cost.

Local Data Integration in East Central Florida

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Manobianco, John T.

1999-01-01

The Applied Meteorology Unit has configured a Local Data Integration System (LDIS) for east central Florida which assimilates in-situ and remotely-sensed observational data into a series of high-resolution gridded analyses. The ultimate goal for running LDIS is to generate products that may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of the 45th Weather Squadron (45 WS), Spaceflight Meteorology Group (SMG), and the Melbourne National Weather Service (NWS MLB) operational requirements. LDIS has the potential to provide added value for nowcasts and short-ten-n forecasts for two reasons. First, it incorporates all data operationally available in east central Florida. Second, it is run at finer spatial and temporal resolutions than current national-scale operational models such as the Rapid Update Cycle and Eta models. LDIS combines all available data to produce grid analyses of primary variables (wind, temperature, etc.) at specified temporal and spatial resolutions. These analyses of primary variables can be used to compute diagnostic quantities such as vorticity and divergence. This paper demonstrates the utility of LDIS over east central Florida for a warm season case study. The evolution of a significant thunderstorm outflow boundary is depicted through horizontal and vertical cross section plots of wind speed, divergence, and circulation. In combination with a suitable visualization too], LDIS may provide users with a more complete and comprehensive understanding of evolving mesoscale weather than could be developed by individually examining the disparate data sets over the same area and time.

Fine-scale natal homing and localized movement as shaped by sex and spawning habitat in chinook salmon

USGS Publications Warehouse

Neville, Helen; Isaak, Daniel; Dunham, J.B.; Thurow, Russel; Rieman, B.

2006-01-01

Natal homing is a hallmark of the life history of salmonid fishes, but the spatial scale of homing within local, naturally reproducing salmon populations is still poorly understood. Accurate homing (paired with restricted movement) should lead to the existence of fine-scale genetic structuring due to the spatial clustering of related individuals on spawning grounds. Thus, we explored the spatial resolution of natal homing using genetic associations among individual Chinook salmon (Oncorhynchus tshawytscha) in an interconnected stream network. We also investigated the relationship between genetic patterns and two factors hypothesized to influence natal homing and localized movements at finer scales in this species, localized patterns in the distribution of spawning gravels and sex. Spatial autocorrelation analyses showed that spawning locations in both sub-basins of our study site were spatially clumped, but the upper sub-basin generally had a larger spatial extent and continuity of redd locations than the lower sub-basin, where the distribution of redds and associated habitat conditions were more patchy. Male genotypes were not autocorrelated at any spatial scale in either sub-basin. Female genotypes showed significant spatial autocorrelation and genetic patterns for females varied in the direction predicted between the two sub-basins, with much stronger autocorrelation in the sub-basin with less continuity in spawning gravels. The patterns observed here support predictions about differential constraints and breeding tactics between the two sexes and the potential for fine-scale habitat structure to influence the precision of natal homing and localized movements of individual Chinook salmon on their breeding grounds.

Scaling range sizes to threats for robust predictions of risks to biodiversity.

PubMed

Keith, David A; Akçakaya, H Resit; Murray, Nicholas J

2018-04-01

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range-size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red-list assessments for decades, appropriate spatial scales of AOO for predicting risks of species' extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale-sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1-1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer-scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid-measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape-scale threats to species and ecosystems. © 2017 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology

USGS Publications Warehouse

Cross, Paul C.; Klaver, Robert W.; Brennan, Angela; Creel, Scott; Beckmann, Jon P.; Higgs, Megan D.; Scurlock, Brandon M.

2013-01-01

Abstract. It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model’s resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

DEFINING RECOVERY GOALS AND STRATEGIES FOR ENDANGERED SPECIES USING SPATIALLY-EXPLICIT POPULATION MODELS

EPA Science Inventory

We used a spatially explicit population model of wolves (Canis lupus) to propose a framework for defining rangewide recovery priorities and finer-scale strategies for regional reintroductions. The model predicts that Yellowstone and central Idaho, where wolves have recently been ...

Multiple energetic injections in a strong spike-like solar burst

NASA Technical Reports Server (NTRS)

Kaufmann, P.; Correia, E.; Costa, J. E. R.; Dennis, B. R.; Hurford, G. J.; Brown, J. C.

1984-01-01

An intense and fast spike-like solar burst was built up of short time scale structures superimposed on an underlying gradual emission, the time evolution of which shows remarkable proportionality between hard X-ray and microwave fluxes. The finer time structures were best defined at mm-microwaves. At the peak of the event, the finer structures repeat every 30 x 60 ms. The more slowly varying component with a time scale of about 1 second was identified in microwave hard X-rays throughout the burst duration. It is suggested that X-ray fluxes might also be proportional to the repetition rate of basic units of energy injection (quasi-quantized). The relevant parameters of one primary energy release site are estimated both in the case where hard X-rays are produced primarily by thick-target bremsstrahlung, and when they are purely thermal. The relation of this figure to global energy considerations is discussed. Previously announced in STAR as N83-35983

Sounds different: inbreeding depression in sexually selected traits in the cricket Teleogryllus commodus.

PubMed

Drayton, J M; Hunt, J; Brooks, R; Jennions, M D

2007-05-01

If male sexual signalling is honest because it captures genetic variation in condition then traits that are important mate choice cues should be disproportionately affected by inbreeding relative to other traits. To test this, we investigated the effect of brother-sister mating on advertisement calling by male field crickets Teleogryllus commodus. We quantified the effect of one generation of inbreeding on nightly calling effort and five finer-scale aspects of call structure that have been shown to influence attractiveness. We also quantified inbreeding depression on six life history traits and one morphological trait. Inbreeding significantly reduced hatching success, nymph survival and adult lifespan but had no detectable effect on hatching rate, developmental rate or adult body mass. The effect of inbreeding on sexually selected traits was equivocal. There was no decline in calling effort (seconds of sound production/night) by inbred males, but there were highly significant changes in three of five finer-scale call parameters. Sexually selected traits clearly vary in their susceptibility to inbreeding depression.

Grid Sensitivity Study for Slat Noise Simulations

NASA Technical Reports Server (NTRS)

Lockard, David P.; Choudhari, Meelan M.; Buning, Pieter G.

2014-01-01

The slat noise from the 30P/30N high-lift system is being investigated through computational fluid dynamics simulations in conjunction with a Ffowcs Williams-Hawkings acoustics solver. Many previous simulations have been performed for the configuration, and the case was introduced as a new category for the Second AIAA workshop on Benchmark problems for Airframe Noise Configurations (BANC-II). However, the cost of the simulations has restricted the study of grid resolution effects to a baseline grid and coarser meshes. In the present study, two different approaches are being used to investigate the effect of finer resolution of near-field unsteady structures. First, a standard grid refinement by a factor of two is used, and the calculations are performed by using the same CFL3D solver employed in the majority of the previous simulations. Second, the OVERFLOW code is applied to the baseline grid, but with a 5th-order upwind spatial discretization as compared with the second-order discretization used in the CFL3D simulations. In general, the fine grid CFL3D simulation and OVERFLOW calculation are in very good agreement and exhibit the lowest levels of both surface pressure fluctuations and radiated noise. Although the smaller scales resolved by these simulations increase the velocity fluctuation levels, they appear to mitigate the influence of the larger scales on the surface pressure. These new simulations are used to investigate the influence of the grid on unsteady high-lift simulations and to gain a better understanding of the physics responsible for the noise generation and radiation.

Validation of non-stationary precipitation series for site-specific impact assessment: comparison of two statistical downscaling techniques

NASA Astrophysics Data System (ADS)

Mullan, Donal; Chen, Jie; Zhang, Xunchang John

2016-02-01

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

Classification of JERS-1 Image Mosaic of Central Africa Using A Supervised Multiscale Classifier of Texture Features

NASA Technical Reports Server (NTRS)

Saatchi, Sassan; DeGrandi, Franco; Simard, Marc; Podest, Erika

1999-01-01

In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.

Estimation of Satellite-Based SO42- and NH4+ Composition of Ambient Fine Particulate Matter Over China Using Chemical Transport Model

NASA Astrophysics Data System (ADS)

Si, Y.; Li, S.; Chen, L.; Yu, C.; Zhu, W.

2018-04-01

Epidemiologic and health impact studies have examined the chemical composition of ambient PM2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM2.5 data with a spatial resolution of 0.1° × 0.1°, we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of -35.9 %, NME of 48.2 %, ARB_50 % of 53.68 % for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO42- and NH4+ concentrations and time series of monthly average concentrations were also investigated. On a national scale, both exhibited a downward trend each year between 2004 and 2014 (SO42-: -0.61 %; NH4+: -0.21 %), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004-2007 and 2008-2011, followed by a negative trend over the period 2012-2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as follows: winter > summer > autumn > spring. High concentrations of these species were concentrated in the NCP and SCB, originating from coal-fired power plants and agricultural activities, respectively. Efforts to reduce sulfur dioxide (SO2) emissions have yielded remarkable results since the government has adopted stricter control measures in recent years. Moreover, ammonia emissions should be controlled while reducing the concentration of sulfur, nitrogen and particulate matter. This study provides an assessment of the population's exposure to certain chemical components.

Eddy Effects in the General Circulation, Spanning Mean Currents, Mesoscale Eddies, and Topographic Generation, Including Submesoscale Nests

DTIC Science & Technology

2014-09-30

against real-world data in cooperation with William S. Kessler and Hristina Hristova from PMEL (Solomon Sea), and Satoshi Mitarai and Taichi Sakagami from...refined grids, starting with basin-wide eddy permitting resolutions (although substantially finer than that used in climate modeling), and downscaling it...instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send

Synthesis of Road Networks by Data Conflation

DTIC Science & Technology

2014-04-01

Transform requires basic trigonometric properties. Suppose we have a line oriented as shown in Figure 9 then by defining the parameters, ρ, and θ we...location. Rather than searching for the remaining three parameters, the major and minor axes and the orientation angle, the axes ratio is utilized to...axes ratio and orientation angle are searched on a coarse quantization level and then the local maxima are obtained and a finer resolution area is

Subsurface Monitoring of CO2 Sequestration - A Review and Look Forward

NASA Astrophysics Data System (ADS)

Daley, T. M.

2012-12-01

The injection of CO2 into subsurface formations is at least 50 years old with large-scale utilization of CO2 for enhanced oil recovery (CO2-EOR) beginning in the 1970s. Early monitoring efforts had limited measurements in available boreholes. With growing interest in CO2 sequestration beginning in the 1990's, along with growth in geophysical reservoir monitoring, small to mid-size sequestration monitoring projects began to appear. The overall goals of a subsurface monitoring plan are to provide measurement of CO2 induced changes in subsurface properties at a range of spatial and temporal scales. The range of spatial scales allows tracking of the location and saturation of the plume with varying detail, while finer temporal sampling (up to continuous) allows better understanding of dynamic processes (e.g. multi-phase flow) and constraining of reservoir models. Early monitoring of small scale pilots associated with CO2-EOR (e.g., the McElroy field and the Lost Hills field), developed many of the methodologies including tomographic imaging and multi-physics measurements. Large (reservoir) scale sequestration monitoring began with the Sleipner and Weyburn projects. Typically, large scale monitoring, such as 4D surface seismic, has limited temporal sampling due to costs. Smaller scale pilots can allow more frequent measurements as either individual time-lapse 'snapshots' or as continuous monitoring. Pilot monitoring examples include the Frio, Nagaoka and Otway pilots using repeated well logging, crosswell imaging, vertical seismic profiles and CASSM (continuous active-source seismic monitoring). For saline reservoir sequestration projects, there is typically integration of characterization and monitoring, since the sites are not pre-characterized resource developments (oil or gas), which reinforces the need for multi-scale measurements. As we move beyond pilot sites, we need to quantify CO2 plume and reservoir properties (e.g. pressure) over large scales, while still obtaining high resolution. Typically the high-resolution (spatial and temporal) tools are deployed in permanent or semi-permanent borehole installations, where special well design may be necessary, such as non-conductive casing for electrical surveys. Effective utilization of monitoring wells requires an approach of modular borehole monitoring (MBM) were multiple measurements can be made. An example is recent work at the Citronelle pilot injection site where an MBM package with seismic, fluid sampling and distributed fiber sensing was deployed. For future large scale sequestration monitoring, an adaptive borehole-monitoring program is proposed.

Flash flooding: Toward an Interdisciplinary and Integrated Strategy for Disaster Reduction in a Global Environmental Change Perspective

NASA Astrophysics Data System (ADS)

Ruin, Isabelle

2014-05-01

How do people answer to heavy precipitation and flood warnings? How do they adapt their daily schedule and activity to the fast evolution of the environmental circumstances? More generally, how do social processes interact with physical ones? Such questions address the dynamical interactions between hydro-meteorological variables, human perception and representation of the environment, and actual individual and social behavioral responses. It also poses the question of scales and hierarchy issues through seamless interactions between smaller and larger scales. These questions are relevant for both social and physical scientists. They are more and more pertinently addressed in the Global Environmental Change perspective through the concepts of Coupled Human And Natural Systems (CHANS), resilience or panarchy developped in the context of interdisciplinary collaborations. Nevertheless those concepts are complex and not easy to handle, specially when facing with operational goals. One of the main difficulty to advance these integrated approaches is the access to empirical data informing the processes at various scales. In fact, if physical and social processes are well studied by distinct disciplines, they are rarely jointly explored within similar spatial and temporal resolutions. Such coupled observation and analysis poses methodological challenges, specially when dealing with responses to short-fuse and extreme weather events. In fact, if such coupled approach is quite common to study large scale phenomenon like global change (for instance using historical data on green house gaz emissions and the evolution of temperatures worldwide), it is rarer for studing smaller nested sets of scales of human-nature systems where finer resolution data are sparse. Another problem arise from the need to produce comparable analysis on different case studies where social, physical and even cultural contexts may be diverse. Generic and robust framework for data collection, modeling and analysis are needed to allow cross comparison and deeper understanding of the processes accross scales. This presentation will address these issues based on concrete exemples from empirical studies on past flash flooding events across Europe and USA.

Sub-seismic scale folding and thrusting within an exposed mass transport deposit: A case study from NW Argentina

NASA Astrophysics Data System (ADS)

Sobiesiak, Matheus S.; Alsop, G. Ian; Kneller, Ben; Milana, Juan Pablo

2017-03-01

While imaging of mass transport deposits (MTDs) by seismic reflection techniques commonly reveals thrusts and large blocks that affect entire deposits, associated systems of folds are generally less apparent as they are typically below the limits of seismic resolution. However, such sub-seismic scale structures are important as they permit the direction of emplacement, gross kinematics and internal strain within MTDs to be determined. Here we present a rigorous description of two outcrop-scale MTDs exposed in La Peña gorge, northwestern Argentina. These Carboniferous MTDs enable us to illustrate structural changes from a compressional domain, marked by sets of imbricated sandstone layers, into an extensional domain, characterized by sheared blocks of sandstone embedded in a finer matrix. Folds may be progressively modified during slump translation, resulting in asymmetric folds, which undergo subsequent deformation leading to sheared fold limbs together with detached and rotated fold hinges. In order to constrain transport directions within the MTDs, we measured fold hinges, mud clast alignment, and thrust planes as kinematic indicators. We propose emplacement models for both MTDs based on the overall deformational behaviour of sandstone beds during translation. The first model is based on the internal geometries and structures of a fault-dominated MTD, and the second model is based on layer-normal shearing in a fold-dominated MTD.

Field Assessment of the Village Green Project: An Autonomous Community Air Quality Monitoring System

EPA Science Inventory

Recent findings on air pollution levels in communities motivate new technologies to assess air pollution at finer spatial scale. The Village Green Project (VGP) is a novel approach using commercially-available technology for long-term community environments air pollution measure...

Multiscale measurement error models for aggregated small area health data.

PubMed

Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

2016-08-01

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.

Automated Transmission-Mode Scanning Electron Microscopy (tSEM) for Large Volume Analysis at Nanoscale Resolution

PubMed Central

Kuwajima, Masaaki; Mendenhall, John M.; Lindsey, Laurence F.; Harris, Kristen M.

2013-01-01

Transmission-mode scanning electron microscopy (tSEM) on a field emission SEM platform was developed for efficient and cost-effective imaging of circuit-scale volumes from brain at nanoscale resolution. Image area was maximized while optimizing the resolution and dynamic range necessary for discriminating key subcellular structures, such as small axonal, dendritic and glial processes, synapses, smooth endoplasmic reticulum, vesicles, microtubules, polyribosomes, and endosomes which are critical for neuronal function. Individual image fields from the tSEM system were up to 4,295 µm2 (65.54 µm per side) at 2 nm pixel size, contrasting with image fields from a modern transmission electron microscope (TEM) system, which were only 66.59 µm2 (8.160 µm per side) at the same pixel size. The tSEM produced outstanding images and had reduced distortion and drift relative to TEM. Automated stage and scan control in tSEM easily provided unattended serial section imaging and montaging. Lens and scan properties on both TEM and SEM platforms revealed no significant nonlinear distortions within a central field of ∼100 µm2 and produced near-perfect image registration across serial sections using the computational elastic alignment tool in Fiji/TrakEM2 software, and reliable geometric measurements from RECONSTRUCT™ or Fiji/TrakEM2 software. Axial resolution limits the analysis of small structures contained within a section (∼45 nm). Since this new tSEM is non-destructive, objects within a section can be explored at finer axial resolution in TEM tomography with current methods. Future development of tSEM tomography promises thinner axial resolution producing nearly isotropic voxels and should provide within-section analyses of structures without changing platforms. Brain was the test system given our interest in synaptic connectivity and plasticity; however, the new tSEM system is readily applicable to other biological systems. PMID:23555711

Using High Resolution Model Data to Improve Lightning Forecasts across Southern California

NASA Astrophysics Data System (ADS)

Capps, S. B.; Rolinski, T.

2014-12-01

Dry lightning often results in a significant amount of fire starts in areas where the vegetation is dry and continuous. Meteorologists from the USDA Forest Service Predictive Services' program in Riverside, California are tasked to provide southern and central California's fire agencies with fire potential outlooks. Logistic regression equations were developed by these meteorologists several years ago, which forecast probabilities of lightning as well as lightning amounts, out to seven days across southern California. These regression equations were developed using ten years of historical gridded data from the Global Forecast System (GFS) model on a coarse scale (0.5 degree resolution), correlated with historical lightning strike data. These equations do a reasonably good job of capturing a lightning episode (3-5 consecutive days or greater of lightning), but perform poorly regarding more detailed information such as exact location and amounts. It is postulated that the inadequacies in resolving the finer details of episodic lightning events is due to the coarse resolution of the GFS data, along with limited predictors. Stability parameters, such as the Lifted Index (LI), the Total Totals index (TT), Convective Available Potential Energy (CAPE), along with Precipitable Water (PW) are the only parameters being considered as predictors. It is hypothesized that the statistical forecasts will benefit from higher resolution data both in training and implementing the statistical model. We have dynamically downscaled NCEP FNL (Final) reanalysis data using the Weather Research and Forecasting model (WRF) to 3km spatial and hourly temporal resolution across a decade. This dataset will be used to evaluate the contribution to the success of the statistical model of additional predictors in higher vertical, spatial and temporal resolution. If successful, we will implement an operational dynamically downscaled GFS forecast product to generate predictors for the resulting statistical lightning model. This data will help fire agencies be better prepared to pre-deploy resources in advance of these events. Specific information regarding duration, amount, and location will be especially valuable.

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.

The Super Tuesday Outbreak: Forecast Sensitivities to Single-Moment Microphysics Schemes

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Case, Jonathan L.; Dembek, Scott R.; Jedlovec, Gary J.; Lapenta, William M.

2008-01-01

Forecast precipitation and radar characteristics are used by operational centers to guide the issuance of advisory products. As operational numerical weather prediction is performed at increasingly finer spatial resolution, convective precipitation traditionally represented by sub-grid scale parameterization schemes is now being determined explicitly through single- or multi-moment bulk water microphysics routines. Gains in forecasting skill are expected through improved simulation of clouds and their microphysical processes. High resolution model grids and advanced parameterizations are now available through steady increases in computer resources. As with any parameterization, their reliability must be measured through performance metrics, with errors noted and targeted for improvement. Furthermore, the use of these schemes within an operational framework requires an understanding of limitations and an estimate of biases so that forecasters and model development teams can be aware of potential errors. The National Severe Storms Laboratory (NSSL) Spring Experiments have produced daily, high resolution forecasts used to evaluate forecast skill among an ensemble with varied physical parameterizations and data assimilation techniques. In this research, high resolution forecasts of the 5-6 February 2008 Super Tuesday Outbreak are replicated using the NSSL configuration in order to evaluate two components of simulated convection on a large domain: sensitivities of quantitative precipitation forecasts to assumptions within a single-moment bulk water microphysics scheme, and to determine if these schemes accurately depict the reflectivity characteristics of well-simulated, organized, cold frontal convection. As radar returns are sensitive to the amount of hydrometeor mass and the distribution of mass among variably sized targets, radar comparisons may guide potential improvements to a single-moment scheme. In addition, object-based verification metrics are evaluated for their utility in gauging model performance and QPF variability.

On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates

USGS Publications Warehouse

Singh, Ramesh K.; Senay, Gabriel B.; Velpuri, Naga Manohar; Bohms, Stefanie; Verdin, James P.

2014-01-01

 Downscaling is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for downscaling MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and downscaling. The regression with intercept method does have limitations in downscaling if the slope and intercept are computed over a large area. A good agreement was obtained between downscaled monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from −16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and downscaled monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between downscaled monthly AET using LinZI method and the gridded FLUXNET dataset. The downscaled monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed downscaling method will be very useful in advancing the application of remotely sensed images in water resources planning and management.

Astronomical constraints on global carbon-cycle perturbation during Oceanic Anoxic Event 2 (OAE2)

NASA Astrophysics Data System (ADS)

Li, Yong-Xiang; Montañez, Isabel P.; Liu, Zhonghui; Ma, Lifeng

2017-03-01

Oceanic Anoxic Event 2 (OAE2) was a major disturbance in global carbon cycling and transient climate disruption, triggered by a pulse of volcanic CO2. Although this well-studied perturbation to the ocean-atmosphere system offers a unique opportunity to better understand abrupt climate change in response to CO2-forcing, the origin, evolution and duration of the event are still debated due in large part to the temporal resolution of existing OAE2 records and uncertainty over the duration of the overall perturbation and C cycle shifts within it. Here we report coupled magnetic susceptibility (MS) and carbon-isotope time-series of ∼2.5 to 5 ± 0.5kyr resolution from an expanded OAE2 interval from southern Tibet, China. MS cyclicity indicates short eccentricity modulation, permitting the construction of a high-precision orbital timescale which, when integrated with the high resolution δ13Ccarb record, fully constrains the timing and nature of onset through recovery of OAE2, revealing finer-scale structure than previously recognized. Abrupt coupled shifts in δ13Ccarb and MS, and changing phase relationships in-step with transitions between high and low long eccentricity, indicate orbitally linked changes in marine carbon cycling and monsoon dynamics superimposed on repeated wholesale oceanographic changes. In particular, the high-resolution Tibetan record reveals dynamic shifts in the phasing relationship of MS and δ13 C, which suggests that the initiation of ocean anoxia was probably not orbitally forced. This finding is in sharp contrast with the paradigm of orbitally forced ocean anoxia. Conversely, the new record suggests that termination of anoxia was likely orbitally forced and superimposed on a dramatic oceanographic change.

Geographically weighted regression based methods for merging satellite and gauge precipitation

NASA Astrophysics Data System (ADS)

Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

2018-03-01

Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

3D visualization of ultra-fine ICON climate simulation data

NASA Astrophysics Data System (ADS)

Röber, Niklas; Spickermann, Dela; Böttinger, Michael

2016-04-01

Advances in high performance computing and model development allow the simulation of finer and more detailed climate experiments. The new ICON model is based on an unstructured triangular grid and can be used for a wide range of applications, ranging from global coupled climate simulations down to very detailed and high resolution regional experiments. It consists of an atmospheric and an oceanic component and scales very well for high numbers of cores. This allows us to conduct very detailed climate experiments with ultra-fine resolutions. ICON is jointly developed in partnership with DKRZ by the Max Planck Institute for Meteorology and the German Weather Service. This presentation discusses our current workflow for analyzing and visualizing this high resolution data. The ICON model has been used for eddy resolving (<10km) ocean simulations, as well as for ultra-fine cloud resolving (120m) atmospheric simulations. This results in very large 3D time dependent multi-variate data that need to be displayed and analyzed. We have developed specific plugins for the free available visualization software ParaView and Vapor, which allows us to read and handle that much data. Within ParaView, we can additionally compare prognostic variables with performance data side by side to investigate the performance and scalability of the model. With the simulation running in parallel on several hundred nodes, an equal load balance is imperative. In our presentation we show visualizations of high-resolution ICON oceanographic and HDCP2 atmospheric simulations that were created using ParaView and Vapor. Furthermore we discuss our current efforts to improve our visualization capabilities, thereby exploring the potential of regular in-situ visualization, as well as of in-situ compression / post visualization.

The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.

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

Drover, Damion, Ryan

2011-12-01

One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would thereforemore » be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a laser altimetry remote sensing method, obtained from the USDA Forest Service at Savannah River Site. The specific DEM resolutions were chosen because they are common grid cell sizes (10m, 30m, and 50m) used in mapping for management applications and in research. The finer resolutions (2m and 5m) were chosen for the purpose of determining how finer resolutions performed compared with coarser resolutions at predicting wetness and related soil attributes. The wetness indices were compared across DEMs and with each other in terms of quantile and distribution differences, then in terms of how well they each correlated with measured soil attributes. Spatial and non-spatial analyses were performed, and predictions using regression and geostatistics were examined for efficacy relative to each DEM resolution. Trends in the raw data and analysis results were also revealed.« less

The Importance and Current Limitations of Planetary Boundary Layer (PBL) Retrieval from Space for Land-Atmosphere Coupling Studies

NASA Astrophysics Data System (ADS)

Santanello, J. A., Jr.; Schaefer, A.

2016-12-01

There is an established need for improved PBL remote sounding over land for hydrology, land-atmosphere (L-A), PBL, cloud/convection, pollution/chemistry studies and associated model evaluation and development. Most notably, the connection of surface hydrology (through soil moisture) to clouds and precipitation relies on proper quantification of water's transport through the coupled system, which is modulated strongly by PBL structure, growth, and feedback processes such as entrainment. In-situ (ground-based or radiosonde) measurements will be spatially limited to small field campaigns for the foreseeable future, so satellite data is a must in order to understand these processes globally. The scales of these applications require diurnal resolution (e.g. 3-hourly or finer) at <100m vertical and 1-10km spatial resolutions in order to assess processes driving land-PBL coupling and water and energy cycles at their native scales. Today's satellite sensors (e.g. advanced IR, GEO, lidar, GPS-RO) do not reach close to these targets in terms of accuracy or resolution, and each of these sensors has some advantages but even more limitations that make them impractical for PBL and L-A studies. Unfortunately, there is very little attention or planning (short or long-term) in place for improving lower tropospheric sounding over land, and as a result PBL and L-A interactions have been identified as `gaps' in current programmatic focal areas. It is therefore timely to assess how these technologies can be leveraged, combined, or evolved in order to form a dedicated mission or sub-mission to routinely monitor the PBL on diurnal timescales. In addition, improved PBL monitoring from space needs to be addressed in the next Decadal Survey. In this talk, the importance of PBL information (structure, evolution) for L-A coupling diagnostics and model development will be summarized. The current array of PBL retrieval methods and products from space will then be assessed in terms of meeting the needs of these models, diagnostics, and scales, with a look forward as to how this can and must be improved through future mission and sensor design.

Reactivity of Aluminum-Based Mixtures with Early Transition Metals

DTIC Science & Technology

2014-08-01

particles are no longer equiaxed but lenticular and lammelar. Dimensions of the heavily deformed Ti particles are considerably finer (30 µm in length by...same. The Hf particles look coarse under light milling and attain a more lenticular appearance with heavy milling. There is large-scale mixing in this

Large-scale expensive black-box function optimization

NASA Astrophysics Data System (ADS)

Rashid, Kashif; Bailey, William; Couët, Benoît

2012-09-01

This paper presents the application of an adaptive radial basis function method to a computationally expensive black-box reservoir simulation model of many variables. An iterative proxy-based scheme is used to tune the control variables, distributed for finer control over a varying number of intervals covering the total simulation period, to maximize asset NPV. The method shows that large-scale simulation-based function optimization of several hundred variables is practical and effective.

Mission Concept for the Single Aperture Far-Infrared (SAFIR) Observatory

NASA Technical Reports Server (NTRS)

Benford, Dominic J.; Amato, Michael J.; Mather, John C.; Moseley, S. Harvey, Jr.

2004-01-01

We have developed a preliminary but comprehensive mission concept for SAFIR, as a 10 m-class far-infrared and submillimeter observatory that would begin development later in this decade to meet the needs outlined above. Its operating temperature (< or = 4K) and instrument complement would be optimized to reach the natural sky confusion limit in the far-infrared with diffraction-limited performance down to at least the atmospheric cutoff, lambda > or approx. 40 microns. This would provide a point source sensitivity improvement of several orders of magnitude over that of the Spitzer Space Telescope (previously SIRTF) or the Herschel Space Observatory. Additionally, it would have an angular resolution 12 times finer than that of Spitzer and three times finer than Herschel. This sensitivity and angular resolution are necessary to perform imaging and spectroscopic studies of individual galaxies in the early universe. We have considered many aspects of the SAFIR mission, including the telescope technology (optical design, materials, and packaging), detector needs and technologies, cooling method and required technology developments, attitude and pointing, power systems, launch vehicle, and mission operations. The most challenging requirements for this mission are operating temperature and aperture size of the telescope, and the development of detector arrays. SAFIR can take advantage of much of the technology under development for JWST, but with much less stringent requirements on optical accuracy.

MRO High Resolution Imaging Science Experiment (HiRISE): Instrument Development

NASA Technical Reports Server (NTRS)

Delamere, Alan; Becker, Ira; Bergstrom, Jim; Burkepile, Jon; Day, Joe; Dorn, David; Gallagher, Dennis; Hamp, Charlie; Lasco, Jeffrey; Meiers, Bill

2003-01-01

The primary functional requirement of the HiRISE imager is to allow identification of both predicted and unknown features on the surface of Mars to a much finer resolution and contrast than previously possible. This results in a camera with a very wide swath width, 6km at 300km altitude, and a high signal to noise ratio, >100:1. Generation of terrain maps, 30 cm vertical resolution, from stereo images requires very accurate geometric calibration. The project limitations of mass, cost and schedule make the development challenging. In addition, the spacecraft stability must not be a major limitation to image quality. The nominal orbit for the science phase of the mission is a 3pm orbit of 255 by 320 km with periapsis locked to the south pole. The track velocity is approximately 3,400 m/s.

Morphology and kinematics of filaments in Serpens and Perseus molecular clouds: a high resolution study

NASA Astrophysics Data System (ADS)

Dhabal, Arnab; Mundy, Lee; Rizzo, Maxime; Storm, Shaye; Teuben, Peter; CLASSy Collaboration

2018-01-01

Filamentary structures are prevalent in molecular clouds over a wide range of scales, and are often associated with active star formation. The study of filament morphology and kinematics provide insights into the physical processes leading to core formation in clustered environments. As part of the CARMA Large Area Star Formation Survey (CLASSy) follow-up, we observed five Herschel filaments in the Serpens Main, Serpens South and NGC1333 molecular clouds using the J=1-0 transitions of dense gas tracers H13CO+, HNC and H13CN. Of these, H13CO+ and H13CN are optically thin and serve as a test of the kinematics previously seen by the CLASSy in N2H+. The observations have an angular resolution of 7'' and a spectral resolution of 0.16 km/s. Although the large scale structure compares well with the CARMA N2H+ (J=1-0) maps and Herschel dust continuum maps, we resolve finer structure within the filaments identified by Herschel. Most regions are found to have multiple structures and filaments partially overlapping in the line-of-sight. In two regions overlapping structures have velocity differences as high as 1.4 km/s. We identify 8 individual filaments with typical widths of 0.03-0.06 pc in these tracers, which is significantly less than widths observed in the Herschel dust column density maps. At least 50% of the filaments have distinct velocity gradients perpendicular to their major axis with average values in the range 4-10 km s-1 pc-1. These findings are in support of the theoretical models of filament formation by 2-D inflow in the shock layer created by colliding turbulent cells. We also find evidence of velocity gradients along the length of two filaments; the gradients suggest that these filaments are inflowing towards the cloud core.

A new map of standardized terrestrial ecosystems of Africa

USGS Publications Warehouse

Sayre, Roger G.; Comer, Patrick; Hak, Jon; Josse, Carmen; Bow, Jacquie; Warner, Harumi; Larwanou, Mahamane; Kelbessa, Ensermu; Bekele, Tamrat; Kehl, Harald; Amena, Ruba; Andriamasimanana, Rado; Ba, Taibou; Benson, Laurence; Boucher, Timothy; Brown, Matthew; Cress, Jill J.; Dassering, Oueddo; Friesen, Beverly A.; Gachathi, Francis; Houcine, Sebei; Keita, Mahamadou; Khamala, Erick; Marangu, Dan; Mokua, Fredrick; Morou, Boube; Mucina, Ladislav; Mugisha, Samuel; Mwavu, Edward; Rutherford, Michael; Sanou, Patrice; Syampungani, Stephen; Tomor, Bojoi; Vall, Abdallahi Ould Mohamed; Vande Weghe, Jean Pierre; Wangui, Eunice; Waruingi, Lucy

2013-01-01

Terrestrial ecosystems and vegetation of Africa were classified and mapped as part of a larger effort and global protocol (GEOSS – the Global Earth Observation System of Systems), which includes an activity to map terrestrial ecosystems of the earth in a standardized, robust, and practical manner, and at the finest possible spatial resolution. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datalayers (including coastline, landforms, surficial lithology, and bioclimates) were developed at spatial and classification resolutions finer than existing similar datalayers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree (CART) inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover. Multi-scale ecosystems were classified and mapped in an increasingly detailed hierarchical framework using vegetation-based concepts of class, subclass, formation, division, and macrogroup levels. The finest vegetation units (macrogroups) classified and mapped in this effort are defined using diagnostic plant species and diagnostic growth forms that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes (FGDC, 2008). The macrogroups are regarded as meso-scale (100s to 10,000s of hectares) ecosystems. A total of 126 macrogroup types were mapped, each with multiple, repeating occurrences on the landscape. The modeling effort was implemented at a base spatial resolution of 90 m. In addition to creating several rich, new continent-wide biophysical datalayers describing African vegetation and ecosystems, our intention was to explore feasible approaches to rapidly moving this type of standardized, continent-wide, ecosystem classification and mapping effort forward.

Mapping global surface water inundation dynamics using synergistic information from SMAP, AMSR2 and Landsat

NASA Astrophysics Data System (ADS)

Du, J.; Kimball, J. S.; Galantowicz, J. F.; Kim, S.; Chan, S.; Reichle, R. H.; Jones, L. A.; Watts, J. D.

2017-12-01

A method to monitor global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fwLBand) retrievals were derived using SMAP H-polarization brightness temperature (Tb) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency Tb observations from AMSR2. The resulting fwLBand global record has high temporal sampling (1-3 days) and 36-km spatial resolution. The fwLBand annual averages corresponded favourably (R=0.84, p<0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly fwLBand averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable fwLBand performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) fwLBand results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m fwLBand retrievals showed favourable classification accuracy for water (commission error 31.84%; omission error 28.08%) and land (commission error 0.82%; omission error 0.99%) and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new fwLBand algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics, potentially benefiting hydrological monitoring, flood assessments, and global climate and carbon modeling.

A high resolution global scale groundwater model

NASA Astrophysics Data System (ADS)

de Graaf, I. E.; Sutanudjaja, E.; Van Beek, L. P.; Bierkens, M. F.

2013-12-01

As the world's largest accessible source of freshwater, groundwater plays a vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and also supplies water for agricultural and industrial activities. During times of drought, the large natural groundwater storage provides a buffer against water shortage and sustains flows to rivers and wetlands, supporting ecosystem habitats and biodiversity. Yet, the current generation of global scale hydrological models (GHMs) do not include a groundwater flow component, although it is a crucial part of the hydrological cycle. Thus, a realistic physical representation of the groundwater system that allows for the simulation of groundwater head dynamics and lateral flows is essential for GHMs that increasingly run at finer resolution. In this study we present a transient global groundwater model with a resolution of 5 arc-minutes (approximately 10 km at the equator) using MODFLOW (McDonald and Harbaugh, 1988). Aquifer schematization and properties of this groundwater model were developed from available global lithological maps and datasets (Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moosdorf, 2013) combined with information about e.g. aquifer thickness and presence of less permeable, impermeable, and semi-impermeable layers. For the parameterization, we relied entirely on available global datasets and did not calibrate the model so that it can equally be expanded to data poor environments. We forced the groundwater model with the output from the global hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the net groundwater recharge and average surface water levels derived from routed channel discharge. We validated simulated groundwater heads with observations, from North America and Australia, resulting in a coefficient of determination of 0.8 and 0.7 respectively. This shows that it is feasible to build a global groundwater model using best available global information, and estimated water table depths are within acceptable accuracy in many parts of the world.

Identification and simulation of space-time variability of past hydrological drought events in the Limpopo River basin, southern Africa

NASA Astrophysics Data System (ADS)

Trambauer, P.; Maskey, S.; Werner, M.; Pappenberger, F.; van Beek, L. P. H.; Uhlenbrook, S.

2014-08-01

Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer-resolution version (0.05° × 0.05°) of the continental-scale hydrological model PCRaster Global Water Balance (PCR-GLOBWB) was set up for the Limpopo River basin, one of the most water-stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse hydrological droughts in the Limpopo River basin in the period 1979-2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily timescale for the entire basin. PCR-GLOBWB was forced with daily precipitation and temperature obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used meteorological drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI), were also computed for different aggregation periods. Results show that a carefully set-up, process-based model that makes use of the best available input data can identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of hydrological droughts and floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the hydrological drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6 and SPI-12 computed together) is found to be a useful measure for identifying agricultural to long-term hydrological droughts in the Limpopo River basin. Additionally, it was possible to undertake a characterisation of the drought severity in the basin, indicated by its time of occurrence, duration and intensity.

Estimation of wetland evapotranspiration in northern New York using infrared thermometry

NASA Astrophysics Data System (ADS)

Hwang, K.; Chandler, D. G.

2016-12-01

Evapotranspiration (ET) is an important component of the water budget and often regarded as a major water loss. In freshwater wetlands, cumulative annual ET can equal precipitation under well-watered conditions. Wetland ET is therefore an important control on contaminant and nutrient transport. Yet, quantification of wetland ET is challenged by complex surface characteristics, diverse plant species and density, and variations in wetland shape and size. As handheld infrared (IR) cameras have become available, studies exploiting the new technology have increased, especially in agriculture and hydrology. The benefits of IR cameras include (1) high spatial resolution, (2) high sample rates, (3) real-time imaging, (4) a constant viewing geometry, and (5) no need for atmosphere and cloud corrections. Compared with traditional methods, infrared thermometer is capable of monitoring at the scale of a small pond or localized plant community. This enables finer scale survey of heterogeneous land surfaces rather than strict dependence on atmospheric variables. Despite this potential, there has been a limited number of studies of ET and drought stress with IR cameras. In this study, the infrared thermometry-based method was applied to estimate ET over wetland plant species in St. Lawrence River Valley, NY. The results are evaluated with traditional methods to test applicability over multiple vegetation species in a same area.

LiDAR-Derived Surface Roughness Signatures of Basaltic Lava Types at the Muliwai a Pele Lava Channel, Mauna Ulu, Hawai'i

NASA Technical Reports Server (NTRS)

Whelley, Patrick L.; Garry, W. Brent; Hamilton, Christopher W.; Bleacher, Jacob E.

2017-01-01

We used light detection and ranging (LiDAR) data to calculate roughness patterns (homogeneity, mean-roughness, and entropy) for five lava types at two different resolutions (1.5 and 0.1 m/pixel). We found that end-member types (a a and pahoehoe) are separable (with 95% confidence) at both scales, indicating that roughness patterns are well suited for analyzing types of lava. Intermediate lavas were also explored, and we found that slabby-pahoehoe is separable from the other end-members using 1.5 m/pixel data, but not in the 0.1 m/pixel analysis. This suggests that the conversion from pahoehoe to slabby-pahoehoe is a meter-scale process, and the finer roughness characteristics of pahoehoe, such as ropes and toes, are not significantly affected. Furthermore, we introduce the ratio ENT/HOM (derived from lava roughness) as a proxy for assessing local lava flow rate from topographic data. High entropy and low homogeneity regions correlate with high flow rate while low entropy and high homogeneity regions correlate with low flow rate.We suggest that this relationship is not directional, rather it is apparent through roughness differences of the associated lava type emplaced at the high and low rates, respectively.

Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model

USGS Publications Warehouse

Jantz, Claire A.; Goetz, Scott J.; Donato, David I.; Claggett, Peter

2010-01-01

This paper presents a fine-scale (30 meter resolution) regional land cover modeling system, based on the SLEUTH cellular automata model, that was developed for a 257000 km2 area comprising the Chesapeake Bay drainage basin in the eastern United States. As part of this effort, we developed a new version of the SLEUTH model (SLEUTH-3r), which introduces new functionality and fit metrics that substantially increase the performance and applicability of the model. In addition, we developed methods that expand the capability of SLEUTH to incorporate economic, cultural and policy information, opening up new avenues for the integration of SLEUTH with other land-change models. SLEUTH-3r is also more computationally efficient (by a factor of 5) and uses less memory (reduced 65%) than the original software. With the new version of SLEUTH, we were able to achieve high accuracies at both the aggregate level of 15 sub-regional modeling units and at finer scales. We present forecasts to 2030 of urban development under a current trends scenario across the entire Chesapeake Bay drainage basin, and three alternative scenarios for a sub-region within the Chesapeake Bay watershed to illustrate the new ability of SLEUTH-3r to generate forecasts across a broad range of conditions.

Accelerated High-Resolution Differential Ion Mobility Separations Using Hydrogen

PubMed Central

Shvartsburg, Alexandre A.; Smith, Richard D.

2011-01-01

The resolving power of differential ion mobility spectrometry (FAIMS) was dramatically increased recently by carrier gases comprising up to 75% He or various vapors, enabling many new applications. However, the need for resolution of complex mixtures is virtually open-ended and many topical analyses demand yet finer separations. Also, the resolving power gains are often at the expense of speed, in particular making high-resolution FAIMS incompatible with online liquid-phase separations. Here, we report FAIMS employing hydrogen, specifically in mixtures with N2 containing up to 90% H2. Such compositions raise the mobilities of all ions and thus the resolving power beyond that previously feasible, while avoiding the electrical breakdown inevitable in He-rich mixtures. The increases in resolving power and ensuing peak resolution are especially significant at H2 fractions above ~50%. Higher resolution can be exchanged for acceleration of the analyses by up to ~4 times, at least. For more mobile species such as multiply-charged peptides, this exchange is presently forced by the constraints of existing FAIMS devices, but future designs optimized for H2 should consistently improve resolution for all analytes. PMID:22074292

Temporal Resolution Needed for Auditory Communication: Measurement With Mosaic Speech

PubMed Central

Nakajima, Yoshitaka; Matsuda, Mizuki; Ueda, Kazuo; Remijn, Gerard B.

2018-01-01

Temporal resolution needed for Japanese speech communication was measured. A new experimental paradigm that can reflect the spectro-temporal resolution necessary for healthy listeners to perceive speech is introduced. As a first step, we report listeners' intelligibility scores of Japanese speech with a systematically degraded temporal resolution, so-called “mosaic speech”: speech mosaicized in the coordinates of time and frequency. The results of two experiments show that mosaic speech cut into short static segments was almost perfectly intelligible with a temporal resolution of 40 ms or finer. Intelligibility dropped for a temporal resolution of 80 ms, but was still around 50%-correct level. The data are in line with previous results showing that speech signals separated into short temporal segments of <100 ms can be remarkably robust in terms of linguistic-content perception against drastic manipulations in each segment, such as partial signal omission or temporal reversal. The human perceptual system thus can extract meaning from unexpectedly rough temporal information in speech. The process resembles that of the visual system stringing together static movie frames of ~40 ms into vivid motion. PMID:29740295

A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall

NASA Astrophysics Data System (ADS)

Lombardo, F.; Volpi, E.; Koutsoyiannis, D.; Serinaldi, F.

2017-06-01

Generating fine-scale time series of intermittent rainfall that are fully consistent with any given coarse-scale totals is a key and open issue in many hydrological problems. We propose a stationary disaggregation method that simulates rainfall time series with given dependence structure, wet/dry probability, and marginal distribution at a target finer (lower-level) time scale, preserving full consistency with variables at a parent coarser (higher-level) time scale. We account for the intermittent character of rainfall at fine time scales by merging a discrete stochastic representation of intermittency and a continuous one of rainfall depths. This approach yields a unique and parsimonious mathematical framework providing general analytical formulations of mean, variance, and autocorrelation function (ACF) for a mixed-type stochastic process in terms of mean, variance, and ACFs of both continuous and discrete components, respectively. To achieve the full consistency between variables at finer and coarser time scales in terms of marginal distribution and coarse-scale totals, the generated lower-level series are adjusted according to a procedure that does not affect the stochastic structure implied by the original model. To assess model performance, we study rainfall process as intermittent with both independent and dependent occurrences, where dependence is quantified by the probability that two consecutive time intervals are dry. In either case, we provide analytical formulations of main statistics of our mixed-type disaggregation model and show their clear accordance with Monte Carlo simulations. An application to rainfall time series from real world is shown as a proof of concept.

Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2013-12-01

Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale. Representative temporal factors are being developed to capture crop-specific NH3 emission variability by combining knowledge of local crop management practices with high resolution cropland and soil maps. This improved spatially and temporally dependent NH3 emission inventory for agricultural fertilization is being prepared as a direct input to a state of the art air quality model to evaluate the effects of agricultural fertilization on regional air quality and atmospheric deposition of reactive nitrogen species.

A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2017-07-01

Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

The Nested Regional Climate Model: An Approach Toward Prediction Across Scales

NASA Astrophysics Data System (ADS)

Hurrell, J. W.; Holland, G. J.; Large, W. G.

2008-12-01

The reality of global climate change has become accepted and society is rapidly moving to questions of consequences on space and time scales that are relevant to proper planning and development of adaptation strategies. There are a number of urgent challenges for the scientific community related to improved and more detailed predictions of regional climate change on decadal time scales. Two important examples are potential impacts of climate change on North Atlantic hurricane activity and on water resources over the intermountain West. The latter is dominated by complex topography, so that accurate simulations of regional climate variability and change require much finer spatial resolution than is provided with state-of-the-art climate models. Climate models also do not explicitly resolve tropical cyclones, even though these storms have dramatic societal impacts and play an important role in regulating climate. Moreover, the debate over the impact of global warming on tropical cyclones has at times been acrimonious, and the lack of hard evidence has left open opportunities for misinterpretation and justification of pre-existing beliefs. These and similar topics are being assessed at NCAR, in partnership with university colleagues, through the development of a Nested Regional Climate Model (NRCM). This is an ambitious effort to combine a state of the science mesoscale weather model (WRF), a high resolution regional ocean modeling system (ROMS), and a climate model (CCSM) to better simulate the complex, multi-scale interactions intrinsic to atmospheric and oceanic fluid motions that are limiting our ability to predict likely future changes in regional weather statistics and climate. The NRCM effort is attracting a large base of earth system scientists together with societal groups as diverse as the Western Governor's Association and the offshore oil industry. All of these groups require climate data on scales of a few kilometers (or less), so that the NRCM program is producing unique data sets of climate change scenarios of immense interest. In addition, all simulations are archived in a form that will be readily accessible to other researchers, thus enabling a wider group to investigate these important issues.

Navigating Earthquake Physics with High-Resolution Array Back-Projection

NASA Astrophysics Data System (ADS)

Meng, Lingsen

Understanding earthquake source dynamics is a fundamental goal of geophysics. Progress toward this goal has been slow due to the gap between state-of-art earthquake simulations and the limited source imaging techniques based on conventional low-frequency finite fault inversions. Seismic array processing is an alternative source imaging technique that employs the higher frequency content of the earthquakes and provides finer detail of the source process with few prior assumptions. While the back-projection provides key observations of previous large earthquakes, the standard beamforming back-projection suffers from low resolution and severe artifacts. This thesis introduces the MUSIC technique, a high-resolution array processing method that aims to narrow the gap between the seismic observations and earthquake simulations. The MUSIC is a high-resolution method taking advantage of the higher order signal statistics. The method has not been widely used in seismology yet because of the nonstationary and incoherent nature of the seismic signal. We adapt MUSIC to transient seismic signal by incorporating the Multitaper cross-spectrum estimates. We also adopt a "reference window" strategy that mitigates the "swimming artifact," a systematic drift effect in back projection. The improved MUSIC back projections allow the imaging of recent large earthquakes in finer details which give rise to new perspectives on dynamic simulations. In the 2011 Tohoku-Oki earthquake, we observe frequency-dependent rupture behaviors which relate to the material variation along the dip of the subduction interface. In the 2012 off-Sumatra earthquake, we image the complicated ruptures involving orthogonal fault system and an usual branching direction. This result along with our complementary dynamic simulations probes the pressure-insensitive strength of the deep oceanic lithosphere. In another example, back projection is applied to the 2010 M7 Haiti earthquake recorded at regional distance. The high-frequency subevents are located at the edges of geodetic slip regions, which are correlated to the stopping phases associated with rupture speed reduction when the earthquake arrests.

Improved human observer performance in digital reconstructed radiograph verification in head and neck cancer radiotherapy.

PubMed

Sturgeon, Jared D; Cox, John A; Mayo, Lauren L; Gunn, G Brandon; Zhang, Lifei; Balter, Peter A; Dong, Lei; Awan, Musaddiq; Kocak-Uzel, Esengul; Mohamed, Abdallah Sherif Radwan; Rosenthal, David I; Fuller, Clifton David

2015-10-01

Digitally reconstructed radiographs (DRRs) are routinely used as an a priori reference for setup correction in radiotherapy. The spatial resolution of DRRs may be improved to reduce setup error in fractionated radiotherapy treatment protocols. The influence of finer CT slice thickness reconstruction (STR) and resultant increased resolution DRRs on physician setup accuracy was prospectively evaluated. Four head and neck patient CT-simulation images were acquired and used to create DRR cohorts by varying STRs at 0.5, 1, 2, 2.5, and 3 mm. DRRs were displaced relative to a fixed isocenter using 0-5 mm random shifts in the three cardinal axes. Physician observers reviewed DRRs of varying STRs and displacements and then aligned reference and test DRRs replicating daily KV imaging workflow. A total of 1,064 images were reviewed by four blinded physicians. Observer errors were analyzed using nonparametric statistics (Friedman's test) to determine whether STR cohorts had detectably different displacement profiles. Post hoc bootstrap resampling was applied to evaluate potential generalizability. The observer-based trial revealed a statistically significant difference between cohort means for observer displacement vector error ([Formula: see text]) and for [Formula: see text]-axis [Formula: see text]. Bootstrap analysis suggests a 15% gain in isocenter translational setup error with reduction of STR from 3 mm to [Formula: see text]2 mm, though interobserver variance was a larger feature than STR-associated measurement variance. Higher resolution DRRs generated using finer CT scan STR resulted in improved observer performance at shift detection and could decrease operator-dependent geometric error. Ideally, CT STRs [Formula: see text]2 mm should be utilized for DRR generation in the head and neck.

Rapid brain MRI acquisition techniques at ultra-high fields

PubMed Central

Setsompop, Kawin; Feinberg, David A.; Polimeni, Jonathan R.

2017-01-01

Ultra-high-field MRI provides large increases in signal-to-noise ratio as well as enhancement of several contrast mechanisms in both structural and functional imaging. Combined, these gains result in a substantial boost in contrast-to-noise ratio that can be exploited for higher spatial resolution imaging to extract finer-scale information about the brain. With increased spatial resolution, however, is a concurrent increased image encoding burden that can cause unacceptably long scan times for structural imaging and slow temporal sampling of the hemodynamic response in functional MRI—particularly when whole-brain imaging is desired. To address this issue, new directions of imaging technology development—such as the move from conventional 2D slice-by-slice imaging to more efficient Simultaneous MultiSlice (SMS) or MultiBand imaging (which can be viewed as “pseudo-3D” encoding) as well as full 3D imaging—have provided dramatic improvements in acquisition speed. Such imaging paradigms provide higher SNR efficiency as well as improved encoding efficiency. Moreover, SMS and 3D imaging can make better use of coil sensitivity information in multi-channel receiver arrays used for parallel imaging acquisitions through controlled aliasing in multiple spatial directions. This has enabled unprecedented acceleration factors of an order of magnitude or higher in these imaging acquisition schemes, with low image artifact levels and high SNR. Here we review the latest developments of SMS and 3D imaging methods and related technologies at ultra-high field for rapid high-resolution functional and structural imaging of the brain. PMID:26835884

Simulation of Boundary-Layer Cumulus and Stratocumulus Clouds using a Cloud-Resolving Model With Low- and Third-Order Turbulence Closures

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man; Cheng, Anning

2007-01-01

The effects of subgrid-scale condensation and transport become more important as the grid spacings increase from those typically used in large-eddy simulation (LES) to those typically used in cloud-resolving models (CRMs). Incorporation of these effects can be achieved by a joint probability density function approach that utilizes higher-order moments of thermodynamic and dynamic variables. This study examines how well shallow cumulus and stratocumulus clouds are simulated by two versions of a CRM that is implemented with low-order and third-order turbulence closures (LOC and TOC) when a typical CRM horizontal resolution is used and what roles the subgrid-scale and resolved-scale processes play as the horizontal grid spacing of the CRM becomes finer. Cumulus clouds were mostly produced through subgrid-scale transport processes while stratocumulus clouds were produced through both subgrid-scale and resolved-scale processes in the TOC version of the CRM when a typical CRM grid spacing is used. The LOC version of the CRM relied upon resolved-scale circulations to produce both cumulus and stratocumulus clouds, due to small subgrid-scale transports. The mean profiles of thermodynamic variables, cloud fraction and liquid water content exhibit significant differences between the two versions of the CRM, with the TOC results agreeing better with the LES than the LOC results. The characteristics, temporal evolution and mean profiles of shallow cumulus and stratocumulus clouds are weakly dependent upon the horizontal grid spacing used in the TOC CRM. However, the ratio of the subgrid-scale to resolved-scale fluxes becomes smaller as the horizontal grid spacing decreases. The subcloud-layer fluxes are mostly due to the resolved scales when a grid spacing less than or equal to 1 km is used. The overall results of the TOC simulations suggest that a 1-km grid spacing is a good choice for CRM simulation of shallow cumulus and stratocumulus.

Evaluation of Moderate-Resolution Imaging Spectroradiometer (MODIS) Snow Albedo Product (MCD43A) over Tundra

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Schaaf, Crystal B.; Chopping, Mark J.; Strahler, Alan H.; Wang, Jindi; Roman, Miguel O.; Rocha, Adrian V.; Woodcock, Curtis E.; Shuai, Yanmin

2012-01-01

This study assesses the MODIS standard Bidirectional Reflectance Distribution Function (BRDF)/Albedo product, and the daily Direct Broadcast BRDF/Albedo algorithm at tundra locations under large solar zenith angles and high anisotropic diffuse illumination and multiple scattering conditions. These products generally agree with ground-based albedo measurements during the snow cover period when the Solar Zenith Angle (SZA) is less than 70deg. An integrated validation strategy, including analysis of the representativeness of the surface heterogeneity, is performed to decide whether direct comparisons between field measurements and 500- m satellite products were appropriate or if the scaling of finer spatial resolution airborne or spaceborne data was necessary. Results indicate that the Root Mean Square Errors (RMSEs) are less than 0.047 during the snow covered periods for all MCD43 albedo products at several Alaskan tundra areas. The MCD43 1- day daily albedo product is particularly well suited to capture the rapidly changing surface conditions during the spring snow melt. Results also show that a full expression of the blue sky albedo is necessary at these large SZA snow covered areas because of the effects of anisotropic diffuse illumination and multiple scattering. In tundra locations with dark residue as a result of fire, the MODIS albedo values are lower than those at the unburned site from the start of snowmelt.

Influence of reanalysis datasets on dynamically downscaling the recent past

NASA Astrophysics Data System (ADS)

Moalafhi, Ditiro B.; Evans, Jason P.; Sharma, Ashish

2017-08-01

Multiple reanalysis datasets currently exist that can provide boundary conditions for dynamic downscaling and simulating local hydro-climatic processes at finer spatial and temporal resolutions. Previous work has suggested that there are two reanalyses alternatives that provide the best lateral boundary conditions for downscaling over southern Africa. This study dynamically downscales these reanalyses (ERA-I and MERRA) over southern Africa to a high resolution (10 km) grid using the WRF model. Simulations cover the period 1981-2010. Multiple observation datasets were used for both surface temperature and precipitation to account for observational uncertainty when assessing results. Generally, temperature is simulated quite well, except over the Namibian coastal plain where the simulations show anomalous warm temperature related to the failure to propagate the influence of the cold Benguela current inland. Precipitation tends to be overestimated in high altitude areas, and most of southern Mozambique. This could be attributed to challenges in handling complex topography and capturing large-scale circulation patterns. While MERRA driven WRF exhibits slightly less bias in temperature especially for La Nina years, ERA-I driven simulations are on average superior in terms of RMSE. When considering multiple variables and metrics, ERA-I is found to produce the best simulation of the climate over the domain. The influence of the regional model appears to be large enough to overcome the small difference in relative errors present in the lateral boundary conditions derived from these two reanalyses.

Using a new high resolution regional model for malaria that accounts for population density and surface hydrology to determine sensitivity of malaria risk to climate drivers

NASA Astrophysics Data System (ADS)

Tompkins, Adrian; Ermert, Volker; Di Giuseppe, Francesca

2013-04-01

In order to better address the role of population dynamics and surface hydrology in the assessment of malaria risk, a new dynamical disease model been developed at ICTP, known as VECTRI: VECtor borne disease community model of ICTP, TRIeste (VECTRI). The model accounts for the temperature impact on the larvae, parasite and adult vector populations. Local host population density affects the transmission intensity, and the model thus reproduces the differences between peri-urban and rural transmission noted in Africa. A new simple pond model framework represents surface hydrology. The model can be used on with spatial resolutions finer than 10km to resolve individual health districts and thus can be used as a planning tool. Results of the models representation of interannual variability and longer term projections of malaria transmission will be shown for Africa. These will show that the model represents the seasonality and spatial variations of malaria transmission well matching a wide range of survey data of parasite rate and entomological inoculation rate (EIR) from across West and East Africa taken in the period prior to large-scale interventions. The model is used to determine the sensitivity of malaria risk to climate variations, both in rainfall and temperature, and then its use in a prototype forecasting system coupled with ECMWF forecasts will be demonstrated.

Genetic Variation of 17 Wild Yellow Perch Populations from the Midwest and East Coast Analyzed Via Microsatellites

USDA-ARS?s Scientific Manuscript database

We used microsatellite loci, including seven newly developed by us, to analyze the population genetic structure of wild yellow perch Perca flavescens from 17 sampling areas in the Upper Midwest and East Coast of the United States. Our results revealed greater genetic differentiation and finer-scale ...

Climate change, ecosystem impacts, and management for Pacific salmon

Treesearch

D.E. Schindler; X. Augerot; E. Fleishman; N.J. Mantua; B. Riddell; M. Ruckelshaus; J. Seeb; M. Webster

2008-01-01

As climate change intensifies, there is increasing interest in developing models that reduce uncertainties in projections of global climate and refine these projections to finer spatial scales. Forecasts of climate impacts on ecosystems are far more challenging and their uncertainties even larger because of a limited understanding of physical controls on biological...

Textual and Discoursal Resources Used in the Essay Genre in Sociology and English

ERIC Educational Resources Information Center

Bruce, Ian

2010-01-01

Research that has examined university assignment writing has varied from large-scale, inventorial surveys across disciplines to more specific, finer-grained analyses of the assignment requirements of specific disciplines. However, while such research has involved surveys of the views and expectations of faculty or the analysis of assignment tasks,…

Evaluating Effectiveness of Green Infrastructure Application of Stormwater Best Management Practices in Protecting Stream Habitat and Biotic Condition in New England

EPA Science Inventory

The US EPA is developing assessment tools to evaluate the effectiveness of green infrastructure (GI) applied in stormwater best management practices (BMPs) at the small watershed (HUC12 or finer) scale. Based on analysis of historical monitoring data using boosted regression tre...

Online Mapping and Perception Algorithms for Multi-robot Teams Operating in Urban Environments

DTIC Science & Technology

2015-01-01

each method on a 2.53 GHz Intel i5 laptop. All our algorithms are hand-optimized, implemented in Java and single threaded. To determine which algorithm...approach would be to label all the pixels in the image with an x, y, z point. However, the angular resolution of the camera is finer than that of the...edge criterion. That is, each edge is either present or absent. In [42], edge existence is further screened by a fixed threshold for angular

DEPSCOR06: A Dispersed Monopropellant Microslug Approach for Discrete Satellite Micropropulsion

DTIC Science & Technology

2010-08-01

microfluidics , a controlled slug formation process represents a virtual ’self- valving ’ mechanism which affords finer resolution than a micro- valve for a... microfluidic flow system to study the effects of geometry and material properties on the microslug formation phenomena. The inspiration for this work is derived...the-shelf microfluidic chip, manufactured by Micralyne, Inc. was used as shown in Figure A-1.1. Figure 1.A.1: Geometry of the Micralyne 50 µm x 20 µm

Preliminary Cost Benefit Assessment of Systems for Detection of Hazardous Weather. Volume I,

DTIC Science & Technology

1981-07-01

not be sufficient for adequate stream flow forecasting , it has important potential for real - time flash flood warning. This was illustrated by the 1977...provide a finer spatial resolution of the gridded data. See Table 9. 42 The results of a demonstration of the real - time capabilities of a radar-man system ...detailed real time measurement capabilities and scope for quantitative forecasting is most likely to provide the degree of lead time required if maximum

Analysis of Long Wave Infrared (LWIR) Soil Data to Predict Reflectance Response

DTIC Science & Technology

2009-08-01

Aridisol red-orange sandy soil 6% x 16% 61 12% smectite Aridisol grey calcareous silty soil x 19% 49 22% smectite ...trace 16% 59 20% smectite ; grain size analysis of fraction finer than 2 mm indicates 35% finer than 20 micrometer (12% finer than 5 micrometer...Entisol red-orange sandy loam/alluvium see comment 8% x 10% 72 7% smectite ; 47% finer than 20 μm (22% finer than 5 μm) Entisol sandy

Evaluating interception of larval pallid sturgeon on the Lower Missouri River- data acquisition, interpolation, and visualization

NASA Astrophysics Data System (ADS)

Bulliner, E. A., IV; Erwin, S. O.; Anderson, B. J.; Wilson, H.; Jacobson, R. B.

2016-12-01

The transition from endogenous to exogenous feeding is an important life-stage transition for many riverine fish larvae. On the Missouri River, U.S., riverine alteration has decreased connectivity between the navigation channel and complex, food-producing and foraging areas on the channel margins, namely shallow side channels and sandbar complexes. A favored hypothesis, the interception hypothesis, for recruitment failure of pallid sturgeon is that drifting larvae are not able to exit the highly engineered navigation channel, and therefore starve. We present work exploring measures of hydraulic connectivity between the navigation channel and channel margins using multiple data-collection protocols with acoustic Doppler current profilers (ADCPs). As ADCP datasets alone often do not have high enough spatial resolution to characterize interception and connectivity sufficiently at the scale of drifting sturgeon larvae, they are often supplemented with physical and empirical models. Using boat-mounted ADCPs, we collected 3-dimensional current velocities with a variety of driving techniques (specifically, regularly spaced transects, reciprocal transects, and irregular patterns) around areas of potential larval interception. We then used toolkits based in Python to interpolate 3-dimensional velocity fields at spatial scales finer than the original measurements, and visualized resultant velocity vectors and flowlines in the software package Paraview. Using these visualizations, we investigated the necessary resolution of field measurements required to model connectivity with channel margin areas on large, highly engineered river ecosystems such as the Missouri River. We anticipate that results from this work will be used to help inform models of larval interception under current conditions. Furthermore, results from this work will be useful in developing monitoring strategies to evaluate the restoration of channel complexity to support ecological functions.

Investigating biofilm structure using x-ray microtomography and gratings-based phase contrast

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

Miller, Erin A.; Xiao, Xianghui; Miller, Micah D.

2012-10-17

Direct examination of natural and engineered environments has revealed that the majority of microorganisms in these systems live in structured communities termed biofilms. To gain a better understanding for how biofilms function and interact with their local environment, fundamental capabilities for enhanced visualization, compositional analysis, and functional characterization of biofilms are needed. For pore-scale and community-scale analysis (100’s of nm to 10’s of microns), a variety of surface tools are available. However, understanding biofilm structure in complex three-dimensional (3-D) environments is considerably more difficult. X-ray microtomography can reveal a biofilm’s internal structure, but the obtaining sufficient contrast to image low-Zmore » biological material against a higher-Z substrate makes detecting biofilms difficult. Here we present results imaging Shewanella oneidensis biofilms on a Hollow-fiber Membrane Biofilm Reactor (HfMBR), using the x-ray microtomography system at sector 2-BM of the Advanced Photon Source (APS), at energies ranging from 13-15.4 keV and pixel sizes of 0.7 and 1.3 μm/pixel. We examine the use of osmium (Os) as a contrast agent to enhance biofilm visibility and demonstrate that staining improves imaging of hydrated biofilms. We also present results using a Talbot interferometer to provide phase and scatter contrast information in addition to absorption. Talbot interferometry allows imaging of unstained hydrated biofilms with phase contrast, while absorption contrast primarily highlights edges and scatter contrast provides little information. However, the gratings used here limit the spatial resolution to no finer than 2 μm, which hinders the ability to detect small features. Future studies at higher resolution or higher Talbot order for greater sensitivity to density variations may improve imaging.« less

Spectral Mixture Analysis to map burned areas in Brazil's deforestation arc from 1992 to 2011

NASA Astrophysics Data System (ADS)

Antunes Daldegan, G.; Ribeiro, F.; Roberts, D. A.

2017-12-01

The two most extensive biomes in South America, the Amazon and the Cerrado, are subject to several fire events every dry season. Both are known for their ecological and environmental importance. However, due to the intensive human occupation over the last four decades, they have been facing high deforestation rates. The Cerrado biome is adapted to fire and is considered a fire-dependent landscape. In contrast, the Amazon as a tropical moist broadleaf forest does not display similar characteristics and is classified as a fire-sensitive landscape. Nonetheless, studies have shown that forest areas that have already been burned become more prone to experience recurrent burns. Remote sensing has been extensively used by a large number of researchers studying fire occurrence at a global scale, as well as in both landscapes aforementioned. Digital image processing aiming to map fire activity has been applied to a number of imagery from sensors of various spatial, temporal, and spectral resolutions. More specifically, several studies have used Landsat data to map fire scars in the Amazon forest and in the Cerrado. An advantage of using Landsat data is the potential to map fire scars at a finer spatial resolution, when compared to products derived from imagery of sensors featuring better temporal resolution but coarser spatial resolution, such as MODIS (Moderate Resolution Imaging Spectrometer) and GOES (Geostationary Operational Environmental Satellite). This study aimed to map burned areas present in the Amazon-Cerrado transition zone by applying Spectral Mixture Analysis on Landsat imagery for a period of 20 years (1992-2011). The study area is a subset of this ecotone, centered at the State of Mato Grosso. By taking advantage of the Landsat 5TM and Landsat 7ETM+ imagery collections available in Google Earth Engine platform and applying Spectral Mixture Analysis (SMA) techniques over them permitted to model fire scar fractions and delimitate burned areas. Overlaying yearly burned areas allowed to identify areas with high fire recurrence.

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

NASA Technical Reports Server (NTRS)

Lin, Shian-Jiann; Atlas, Robert (Technical Monitor)

2002-01-01

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 km or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed-shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

NASA Technical Reports Server (NTRS)

Lin, Shian-Jiann; Atlas, Robert (Technical Monitor)

2002-01-01

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 kin or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed- shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Continental-scale river flow in climate models

NASA Technical Reports Server (NTRS)

Miller, James R.; Russell, Gary L.; Caliri, Guilherme

1994-01-01

The hydrologic cycle is a major part of the global climate system. There is an atmospheric flux of water from the ocean surface to the continents. The cycle is closed by return flow in rivers. In this paper a river routing model is developed to use with grid box climate models for the whole earth. The routing model needs an algorithm for the river mass flow and a river direction file, which has been compiled for 4 deg x 5 deg and 2 deg x 2.5 deg resolutions. River basins are defined by the direction files. The river flow leaving each grid box depends on river and lake mass, downstream distance, and an effective flow speed that depends on topography. As input the routing model uses monthly land source runoff from a 5-yr simulation of the NASA/GISS atmospheric climate model (Hansen et al.). The land source runoff from the 4 deg x 5 deg resolution model is quartered onto a 2 deg x 2.5 deg grid, and the effect of grid resolution is examined. Monthly flow at the mouth of the world's major rivers is compared with observations, and a global error function for river flow is used to evaluate the routing model and its sensitivity to physical parameters. Three basinwide parameters are introduced: the river length weighted by source runoff, the turnover rate, and the basinwide speed. Although the values of these parameters depend on the resolution at which the rivers are defined, the values should converge as the grid resolution becomes finer. When the routing scheme described here is coupled with a climate model's source runoff, it provides the basis for closing the hydrologic cycle in coupled atmosphere-ocean models by realistically allowing water to return to the ocean at the correct location and with the proper magnitude and timing.

X-ray structure determination using low-resolution electron microscopy maps for molecular replacement

DOE PAGES

Jackson, Ryan N.; McCoy, Airlie J.; Terwilliger, Thomas C.; ...

2015-07-30

Structures of multi-subunit macromolecular machines are primarily determined by either electron microscopy (EM) or X-ray crystallography. In many cases, a structure for a complex can be obtained at low resolution (at a coarse level of detail) with EM and at higher resolution (with finer detail) by X-ray crystallography. The integration of these two structural techniques is becoming increasingly important for generating atomic models of macromolecular complexes. A low-resolution EM image can be a powerful tool for obtaining the "phase" information that is missing from an X-ray crystallography experiment, however integration of EM and X-ray diffraction data has been technically challenging.more » Here we show a step-by-step protocol that explains how low-resolution EM maps can be placed in the crystallographic unit cell by molecular replacement, and how initial phases computed from the placed EM density are extended to high resolution by averaging maps over non-crystallographic symmetry. As the resolution gap between EM and Xray crystallography continues to narrow, the use of EM maps to help with X-ray crystal structure determination, as described in this protocol, will become increasingly effective.« less

Assessment of radar resolution requirements for soil moisture estimation from simulated satellite imagery. [Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Dobson, M. C.; Moezzi, S.

1982-01-01

Radar simulations were performed at five-day intervals over a twenty-day period and used to estimate soil moisture from a generalized algorithm requiring only received power and the mean elevation of a test site near Lawrence, Kansas. The results demonstrate that the soil moisture of about 90% of the 20-m by 20-m pixel elements can be predicted with an accuracy of + or - 20% of field capacity within relatively flat agricultural portions of the test site. Radar resolutions of 93 m by 100 m with 23 looks or coarser gave the best results, largely because of the effects of signal fading. For the distribution of land cover categories, soils, and elevation in the test site, very coarse radar resolutions of 1 km by 1 km and 2.6 km by 3.1 km gave the best results for wet moisture conditions while a finer resolution of 93 m by 100 m was found to yield superior results for dry to moist soil conditions.

Highly conductive ribbons prepared by stick-slip assembly of organosoluble gold nanoparticles.

PubMed

Lawrence, Jimmy; Pham, Jonathan T; Lee, Dong Yun; Liu, Yujie; Crosby, Alfred J; Emrick, Todd

2014-02-25

Precisely positioning and assembling nanoparticles (NPs) into hierarchical nanostructures is opening opportunities in a wide variety of applications. Many techniques employed to produce hierarchical micrometer and nanoscale structures are limited by complex fabrication of templates and difficulties with scalability. Here we describe the fabrication and characterization of conductive nanoparticle ribbons prepared from surfactant-free organosoluble gold nanoparticles (Au NPs). We used a flow-coating technique in a controlled, stick-slip assembly to regulate the deposition of Au NPs into densely packed, multilayered structures. This affords centimeter-scale long, high-resolution Au NP ribbons with precise periodic spacing in a rapid manner, up to 2 orders-of-magnitude finer and faster than previously reported methods. These Au NP ribbons exhibit linear ohmic response, with conductivity that varies by changing the binding headgroup of the ligands. Controlling NP percolation during sintering (e.g., by adding polymer to retard rapid NP coalescence) enables the formation of highly conductive ribbons, similar to thermally sintered conductive adhesives. Hierarchical, conductive Au NP ribbons represent a promising platform to enable opportunities in sensing, optoelectronics, and electromechanical devices.

The propagation of varied timescale perturbations in landscapes

NASA Astrophysics Data System (ADS)

Bingham, N.; Johnson, K. N.; Bookhagen, B.; Chadwick, O.

2016-12-01

The classic assumption of steady-state landscapes greatly simplifies models of earth-surface processes. Theoretically, steady-state denotes time independence, but in real landscapes steady-state requires a timescale over which to assume (or document) no change. In the past, poor spatiotemporal resolution of eroding landscapes necessitated that shorter timescale perturbations be ignored in favor of regional formulations of rock uplift = erosion, 105, 6 years. Now, novel techniques and technologies provide an opportunity to define local landscape response to various timescales of perturbations; thus, allowing us to consider multiple steady-states on adjacent watersheds or even along a single watershed. This study seeks to identify the physical propagation of varied timescale perturbations in landscapes in order to provide an updated geomorphic context for interpreting critical zone processes. At our study site - Santa Cruz Island (SCI), CA - perturbations include sea level and climate fluctuations over 105 years coupled with pulses of overgrazing and extreme storm events during the last 200 years. Comprehensive knickpoint location maps and dated marine and fill terraces tighten the spatiotemporal constraints on erosion for SCI. In addition, the island hosts a wide range of lithologies, allowing us to compare lithologic effects on landscape response to perturbations. Our study uses lidar point clouds and high resolution (0.25 and 1 m) digital elevation model analysis to segment landscapes by the degree of their response to perturbations. Landscape response is measured by increases in topographic roughness. We ascertain roughness by analyzing the changes in different terrain attributes on multiple spatial scales: catchment, sub-catchments and individual hillslopes. Terrain attributes utilized include slope, curvature, local relief, flowpath length and contributing catchment area. Statistical analysis of these properties indicates narrower ranges in values for regions of relative stability compared to unstable areas. This updated assessment of landscape response leads to a more detailed and nuanced definition of steady-state across landscapes, enabling a finer resolution of process understanding with the critical zone. The classic assumption of steady-state landscapes greatly simplifies models of earth-surface processes. Theoretically, steady-state denotes time independence, but in real landscapes steady-state requires a timescale over which to assume (or document) no change. In the past, poor spatiotemporal resolution of eroding landscapes necessitated that shorter timescale perturbations be ignored in favor of regional formulations of rock uplift = erosion, 105, 6 years. Now, novel techniques and technologies provide an opportunity to define local landscape response to various timescales of perturbations; thus, allowing us to consider multiple steady-states on adjacent watersheds or even along a single watershed. This study seeks to identify the physical propagation of varied timescale perturbations in landscapes in order to provide an updated geomorphic context for interpreting critical zone processes. At our study site - Santa Cruz Island (SCI), CA - perturbations include sea level and climate fluctuations over 105 years coupled with pulses of overgrazing and extreme storm events during the last 200 years. Comprehensive knickpoint location maps and dated marine and fill terraces tighten the spatiotemporal constraints on erosion for SCI. In addition, the island hosts a wide range of lithologies, allowing us to compare lithologic effects on landscape response to perturbations. Our study uses lidar point clouds and high resolution (0.25 and 1 m) digital elevation model analysis to segment landscapes by the degree of their response to perturbations. Landscape response is measured by increases in topographic roughness. We ascertain roughness by analyzing the changes in different terrain attributes on multiple spatial scales: catchment, sub-catchments and individual hillslopes. Terrain attributes utilized include slope, curvature, local relief, flowpath length and contributing catchment area. Statistical analysis of these properties indicates narrower ranges in values for regions of relative stability compared to unstable areas. This updated assessment of landscape response leads to a more detailed and nuanced definition of steady-state across landscapes, enabling a finer resolution of process understanding with the critical zone.

Photo-chemical transport modelling of tropospheric ozone: A review

NASA Astrophysics Data System (ADS)

Sharma, Sumit; Sharma, Prateek; Khare, Mukesh

2017-06-01

Ground level ozone (GLO), a secondary pollutant having adverse impact on human health, ecology, and agricultural productivity, apart from being a major contributor to global warming, has been a subject matter of several studies. In order to identify appropriate strategies to control GLO levels, accurate assessment and prediction is essential, for which elaborate simulation and modelling is required. Several studies have been undertaken in the past to simulate GLO levels at different scales and for various applications. It is important to evaluate these studies, widely spread over in literature. This paper aims to critically review various studies that have been undertaken, especially in the past 15 years (2000-15) to model GLO. The review has been done of the studies that range over different spatial scales - urban to regional and continental to global. It also includes a review of performance evaluation and sensitivity analysis of photo-chemical transport models in order to assess the extent of application of these models and their predictive capability. The review indicates following major findings: (a) models tend to over-estimate the night-time GLO concentrations due to limited titration of GLO with NO within the model; (b) dominance of contribution from far-off regional sources to average ozone concentration in the urban region and higher contribution of local sources during days of high ozone episodes; requiring strategies for controlling precursor emissions at both regional and local scales; (c) greater influence of NOx over VOC in export of ozone from urban regions due to shifting of urban plumes from VOC-sensitive regime to NOx-sensitive as they move out from city centres to neighbouring rural regions; (d) models with finer resolution inputs perform better to a certain extent, however, further improvement in resolutions (beyond 10 km) did not show improvement always; (e) future projections show an increase in GLO concentrations mainly due to rise in temperatures and biogenic VOC emissions.

Analysis of Microhabitat Use for Two Trout Species Using a Combination of Remote Sensing and Passive Integrated transponder Tags

NASA Astrophysics Data System (ADS)

Lokteff, R.; Wheaton, J. M.; Roper, B.; DeMeurichy, K.; Randall, J.

2011-12-01

The Logan River and its tributaries in northern Utah sustain a significant population of the imperiled Bonneville cutthroat trout (Oncorhynchus clarki Utah) as well as invasive brown trout (Salmo trutta). In general, the upper reaches of the system are populated by cutthroat trout and the lower reaches by brown trout. Spawn Creek is a unique tributary in that it supports both of these species throughout the year. The purpose of this study is to identify differences in fine-scale microhabitat that explain utilization patterns of each species of fish. Passive integrated transponder (PIT) tags have been placed in trout over the last 3 years throughout Spawn Creek. Repeat GPS observations of these fish in their habitat during both spawning and non-spawning periods have been acquired over the last 4 years. Non-spawning activity has been captured using mobile PIT tag antennae. GPS observations of cutthroat trout spawning locations have also been recorded. From these observations both spawning and non-spawning "hotspots" have emerged, which appear to be highly correlated with specific microhabitat characteristics. The entire 2.5 km study reach on lower Spawn Creek has been scanned using ground-based light detection and ranging (LiDAR) which covers all observed "hotspots." LiDAR data provides sub-centimeter resolution point clouds from which detailed geometric measurements and topographic analyses can be used to reveal specific aspects of trout habitat. Where bathymetric data is needed, total station bathymetric surveys have been completed at sub-meter resolution. The combination of these data types at known "hotspot" locations provides an opportunity to quantify aspects of the physical environment at a uniquely fine scale relevant to individual fish. New metrics, as well as old metrics resolved at finer scales, will be presented to explain species and life-stage specific habitat "hotspots" in mountain streams.

Potential accuracy of translation estimation between radar and optical images

NASA Astrophysics Data System (ADS)

Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

2015-10-01

This paper investigates the potential accuracy achievable for optical to radar image registration by area-based approach. The analysis is carried out mainly based on the Cramér-Rao Lower Bound (CRLB) on translation estimation accuracy previously proposed by the authors and called CRLBfBm. This bound is now modified to take into account radar image speckle noise properties: spatial correlation and signal-dependency. The newly derived theoretical bound is fed with noise and texture parameters estimated for the co-registered pair of optical Landsat 8 and radar SIR-C images. It is found that difficulty of optical to radar image registration stems more from speckle noise influence than from dissimilarity of the considered kinds of images. At finer scales (and higher speckle noise level), probability of finding control fragments (CF) suitable for registration is low (1% or less) but overall number of such fragments is high thanks to image size. Conversely, at the coarse scale, where speckle noise level is reduced, probability of finding CFs suitable for registration can be as high as 40%, but overall number of such CFs is lower. Thus, the study confirms and supports area-based multiresolution approach for optical to radar registration where coarse scales are used for fast registration "lock" and finer scales for reaching higher registration accuracy. The CRLBfBm is found inaccurate for the main scale due to intensive speckle noise influence. For other scales, the validity of the CRLBfBm bound is confirmed by calculating statistical efficiency of area-based registration method based on normalized correlation coefficient (NCC) measure that takes high values of about 25%.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

Modeling and simulation of storm surge on Staten Island to understand inundation mitigation strategies

USGS Publications Warehouse

Kress, Michael E.; Benimoff, Alan I.; Fritz, William J.; Thatcher, Cindy A.; Blanton, Brian O.; Dzedzits, Eugene

2016-01-01

Hurricane Sandy made landfall on October 29, 2012, near Brigantine, New Jersey, and had a transformative impact on Staten Island and the New York Metropolitan area. Of the 43 New York City fatalities, 23 occurred on Staten Island. The borough, with a population of approximately 500,000, experienced some of the most devastating impacts of the storm. Since Hurricane Sandy, protective dunes have been constructed on the southeast shore of Staten Island. ADCIRC+SWAN model simulations run on The City University of New York's Cray XE6M, housed at the College of Staten Island, using updated topographic data show that the coast of Staten Island is still susceptible to tidal surge similar to those generated by Hurricane Sandy. Sandy hindcast simulations of storm surges focusing on Staten Island are in good agreement with observed storm tide measurements. Model results calculated from fine-scaled and coarse-scaled computational grids demonstrate that finer grids better resolve small differences in the topography of critical hydraulic control structures, which affect storm surge inundation levels. The storm surge simulations, based on post-storm topography obtained from high-resolution lidar, provide much-needed information to understand Staten Island's changing vulnerability to storm surge inundation. The results of fine-scale storm surge simulations can be used to inform efforts to improve resiliency to future storms. For example, protective barriers contain planned gaps in the dunes to provide for beach access that may inadvertently increase the vulnerability of the area.

On the spatial heterogeneity of net ecosystem productivity in complex landscapes

Treesearch

Ryan E. Emanuel; Diego A. Riveros-Iregui; Brian L. McGlynn; Howard E. Epstein

2011-01-01

Micrometeorological flux towers provide spatially integrated estimates of net ecosystem production (NEP) of carbon over areas ranging from several hectares to several square kilometers, but they do so at the expense of spatially explicit information within the footprint of the tower. This finer-scale information is crucial for understanding how physical and biological...

Overview of the National Inventory and Monitoring Applications Center (NIMAC)

Treesearch

Charles T. Scott

2009-01-01

The National Inventory and Monitoring Applications Center (NIMAC) was created by the Forest Inventory and Analysis (FIA) program in 2006. NIMAC addresses a growing need, expressed by FIA partners, for technical assistance in designing and implementing monitoring plans for forests at scales finer than that provided by the FIA standard inventory. NIMAC's goal is to...

Spatial-temporal models for improved county-level annual estimates

Treesearch

Francis Roesch

2009-01-01

The consumers of data derived from extensive forest inventories often seek annual estimates at a finer spatial scale than that which the inventory was designed to provide. This paper discusses a few model-based and model-assisted estimators to consider for county level attributes that can be applied when the sample would otherwise be inadequate for producing low-...

Adaptation strategies and approaches: Chapter 2

Treesearch

Patricia Butler; Chris Swanston; Maria Janowiak; Linda Parker; Matt St. Pierre; Leslie Brandt

2012-01-01

A wealth of information is available on climate change adaptation, but much of it is very broad and of limited use at the finer spatial scales most relevant to land managers. This chapter contains a "menu" of adaptation actions and provides land managers in northern Wisconsin with a range of options to help forest ecosystems adapt to climate change impacts....

Polymerase Chain Reaction (PCR) applications in white pine blister rust resistance screening

Treesearch

Sam Hendricks; Wendy Sutton; Jeffrey Stone; Richard Sniezko; Angelia Kegley; Anna Schoettle

2011-01-01

A goal of breeding programs for resistance to white pine blister rust is the development of multigenic resistance, even if the genetics and mechanisms of resistance may be imperfectly understood. The goal of multigenic resistance has prompted efforts to categorize host resistance reactions at increasingly finer scales, to identify heritable traits that may confer...

Adaptive mesh refinement and adjoint methods in geophysics simulations

NASA Astrophysics Data System (ADS)

Burstedde, Carsten

2013-04-01

It is an ongoing challenge to increase the resolution that can be achieved by numerical geophysics simulations. This applies to considering sub-kilometer mesh spacings in global-scale mantle convection simulations as well as to using frequencies up to 1 Hz in seismic wave propagation simulations. One central issue is the numerical cost, since for three-dimensional space discretizations, possibly combined with time stepping schemes, a doubling of resolution can lead to an increase in storage requirements and run time by factors between 8 and 16. A related challenge lies in the fact that an increase in resolution also increases the dimensionality of the model space that is needed to fully parametrize the physical properties of the simulated object (a.k.a. earth). Systems that exhibit a multiscale structure in space are candidates for employing adaptive mesh refinement, which varies the resolution locally. An example that we found well suited is the mantle, where plate boundaries and fault zones require a resolution on the km scale, while deeper area can be treated with 50 or 100 km mesh spacings. This approach effectively reduces the number of computational variables by several orders of magnitude. While in this case it is possible to derive the local adaptation pattern from known physical parameters, it is often unclear what are the most suitable criteria for adaptation. We will present the goal-oriented error estimation procedure, where such criteria are derived from an objective functional that represents the observables to be computed most accurately. Even though this approach is well studied, it is rarely used in the geophysics community. A related strategy to make finer resolution manageable is to design methods that automate the inference of model parameters. Tweaking more than a handful of numbers and judging the quality of the simulation by adhoc comparisons to known facts and observations is a tedious task and fundamentally limited by the turnaround times required by human intervention and analysis. Specifying an objective functional that quantifies the misfit between the simulation outcome and known constraints and then minimizing it through numerical optimization can serve as an automated technique for parameter identification. As suggested by the similarity in formulation, the numerical algorithm is closely related to the one used for goal-oriented error estimation. One common point is that the so-called adjoint equation needs to be solved numerically. We will outline the derivation and implementation of these methods and discuss some of their pros and cons, supported by numerical results.

An initial assessment of a SMAP soil moisture disaggregation scheme using TIR surface evaporation data over the continental United States

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.

Variability in Regularity: Mining Temporal Mobility Patterns in London, Singapore and Beijing Using Smart-Card Data

PubMed Central

Zhong, Chen; Batty, Michael; Manley, Ed; Wang, Jiaqiu; Wang, Zijia; Chen, Feng; Schmitt, Gerhard

2016-01-01

To discover regularities in human mobility is of fundamental importance to our understanding of urban dynamics, and essential to city and transport planning, urban management and policymaking. Previous research has revealed universal regularities at mainly aggregated spatio-temporal scales but when we zoom into finer scales, considerable heterogeneity and diversity is observed instead. The fundamental question we address in this paper is at what scales are the regularities we detect stable, explicable, and sustainable. This paper thus proposes a basic measure of variability to assess the stability of such regularities focusing mainly on changes over a range of temporal scales. We demonstrate this by comparing regularities in the urban mobility patterns in three world cities, namely London, Singapore and Beijing using one-week of smart-card data. The results show that variations in regularity scale as non-linear functions of the temporal resolution, which we measure over a scale from 1 minute to 24 hours thus reflecting the diurnal cycle of human mobility. A particularly dramatic increase in variability occurs up to the temporal scale of about 15 minutes in all three cities and this implies that limits exist when we look forward or backward with respect to making short-term predictions. The degree of regularity varies in fact from city to city with Beijing and Singapore showing higher regularity in comparison to London across all temporal scales. A detailed discussion is provided, which relates the analysis to various characteristics of the three cities. In summary, this work contributes to a deeper understanding of regularities in patterns of transit use from variations in volumes of travellers entering subway stations, it establishes a generic analytical framework for comparative studies using urban mobility data, and it provides key points for the management of variability by policy-makers intent on for making the travel experience more amenable. PMID:26872333

Variability in Regularity: Mining Temporal Mobility Patterns in London, Singapore and Beijing Using Smart-Card Data.

PubMed

Zhong, Chen; Batty, Michael; Manley, Ed; Wang, Jiaqiu; Wang, Zijia; Chen, Feng; Schmitt, Gerhard

2016-01-01

To discover regularities in human mobility is of fundamental importance to our understanding of urban dynamics, and essential to city and transport planning, urban management and policymaking. Previous research has revealed universal regularities at mainly aggregated spatio-temporal scales but when we zoom into finer scales, considerable heterogeneity and diversity is observed instead. The fundamental question we address in this paper is at what scales are the regularities we detect stable, explicable, and sustainable. This paper thus proposes a basic measure of variability to assess the stability of such regularities focusing mainly on changes over a range of temporal scales. We demonstrate this by comparing regularities in the urban mobility patterns in three world cities, namely London, Singapore and Beijing using one-week of smart-card data. The results show that variations in regularity scale as non-linear functions of the temporal resolution, which we measure over a scale from 1 minute to 24 hours thus reflecting the diurnal cycle of human mobility. A particularly dramatic increase in variability occurs up to the temporal scale of about 15 minutes in all three cities and this implies that limits exist when we look forward or backward with respect to making short-term predictions. The degree of regularity varies in fact from city to city with Beijing and Singapore showing higher regularity in comparison to London across all temporal scales. A detailed discussion is provided, which relates the analysis to various characteristics of the three cities. In summary, this work contributes to a deeper understanding of regularities in patterns of transit use from variations in volumes of travellers entering subway stations, it establishes a generic analytical framework for comparative studies using urban mobility data, and it provides key points for the management of variability by policy-makers intent on for making the travel experience more amenable.

Assessment of village-wise groundwater draft for irrigation: a field-based study in hard-rock aquifers of central India

NASA Astrophysics Data System (ADS)

Ray, R. K.; Syed, T. H.; Saha, Dipankar; Sarkar, B. C.; Patre, A. K.

2017-12-01

Extracted groundwater, 90% of which is used for irrigated agriculture, is central to the socio-economic development of India. A lack of regulation or implementation of regulations, alongside unrecorded extraction, often leads to over exploitation of large-scale common-pool resources like groundwater. Inevitably, management of groundwater extraction (draft) for irrigation is critical for sustainability of aquifers and the society at large. However, existing assessments of groundwater draft, which are mostly available at large spatial scales, are inadequate for managing groundwater resources that are primarily exploited by stakeholders at much finer scales. This study presents an estimate, projection and analysis of fine-scale groundwater draft in the Seonath-Kharun interfluve of central India. Using field surveys of instantaneous discharge from irrigation wells and boreholes, annual groundwater draft for irrigation in this area is estimated to be 212 × 106 m3, most of which (89%) is withdrawn during non-monsoon season. However, the density of wells/boreholes, and consequent extraction of groundwater, is controlled by the existing hydrogeological conditions. Based on trends in the number of abstraction structures (1982-2011), groundwater draft for the year 2020 is projected to be approximately 307 × 106 m3; hence, groundwater draft for irrigation in the study area is predicted to increase by ˜44% within a span of 8 years. Central to the work presented here is the approach for estimation and prediction of groundwater draft at finer scales, which can be extended to critical groundwater zones of the country.

Impact of different convection permitting resolutions on the representation of heavy rainfall over the UK

NASA Astrophysics Data System (ADS)

Fosser, Giorgia; Kendon, Elizabeth; Chan, Steven

2017-04-01

Previous studies (e.g. Ban et al, 2015; Fosser et al, 2015 and 2016; Kendon et al, 2015) have shown that convection permitting models are able to give a much more realistic representation of convection, and are needed to provide reliable projections of future changes in hourly precipitation extremes. In this context, the UKCP18 project aims to provide policy makers with new UK climate change projections at hourly and local scales, thanks to the first ensemble of runs at convection permitting resolution. As a first step, we need to identify a suitable UK domain, resolution and experimental design for the convective-scale ensemble. Thus, a set of 12-years long simulations driven by ERA Interim reanalysis data has been carried out over the UK using the Met Office Unified Model (UM) at different convection permitting resolutions, namely 1.5 km, 2.2 km and 4km. Different nesting strategy and physical adjustments are also tested. Two observational gridded datasets, based on rain gauges and radar, are used for validation. The analysis aims to identify the impacts of the different convection permitting resolutions (as well as domain size and physical settings) on the representation of precipitation, especially when convection is a predominant feature. Moreover, this study tries to determine the physical reasons behind the found differences and hence to determine if there are any benefits of increasing the horizontal resolution within the convection permitting regime in a climatological context. First results show that the 4km model realises many of the benefits of convection-permitting resolution, namely the rainfall fields are much more realistic and the daily timing of rainfall is better captured compared to convection-parameterised models. For mean precipitation metrics, including precipitation conditioned on circulation type, there is little benefit in moving to resolutions finer than 4km. However, there are some key deficiencies at convection-permitting resolution which are notably worse at 4km, namely the tendency for the heaviest events to be too intense and convective showers to be too "blobby". The use of different nesting strategy seems to have a big impact on the results. Bibliography Ban N, Schmidli J, Schär C (2015) Heavy precipitation in a changing climate: Does short-term summer precipitation increase faster? Geophys Res Lett 42:1165-1172. doi: 10.1002/2014GL062588 Fosser G, Khodayar S, Berg P (2015) Benefit of convection permitting climate model simulations in the representation of convective precipitation. Clim Dyn. doi: 10.1007/s00382-014-2242-1 Fosser G, Khodayar S, Berg P (2015) Climate change in the next 30 years: what can a convection-permitting model tell us that we did not already know? Clim Dyn. accepted Kendon EJ, Roberts NM, Fowler HJ, et al (2014) Heavier summer downpours with climate change revealed by weather forecast resolution model. Nat Clim Chang 4:570-576. doi: 10.1038/nclimate2258

Sedimentary Petrography and Facies Analysis at the Shaler Outcrop, Gale Crater, Mars

NASA Astrophysics Data System (ADS)

Edgar, L. A.; Gupta, S.; Rubin, D. M.; Lewis, K. W.; Kocurek, G.; Anderson, R. B.; Bell, J. F.; Dromart, G.; Edgett, K. S.; Grotzinger, J. P.; Hardgrove, C. J.; Kah, L. C.; Leveille, R. J.; Malin, M.; Mangold, N.; Milliken, R.; Minitti, M. E.; Rice, M. S.; Rowland, S. K.; Schieber, J.; Stack, K.; Sumner, D. Y.; Team, M.

2013-12-01

The Mars Science Laboratory Curiosity rover has recently completed an investigation of a large fluvial deposit known informally as the Shaler outcrop (~1 m thick). Curiosity acquired data at the Shaler outcrop during sols 120-121 and 309-324. The Shaler outcrop is comprised of cross-bedded coarse-grained sandstones and recessive finer-grained intervals. Shaler is distinguished from the surrounding units by the presence of resistant beds exhibiting decimeter scale trough cross-bedding. Observations using the Mast Cameras, Mars Hand Lens Imager (MAHLI) and ChemCam Remote Micro Imager (RMI) enable the recognition of several distinct facies. MAHLI images were acquired on five distinct rock targets, and RMI images were acquired at 33 different locations. On the basis of grain size, erosional resistance, color, and sedimentary structures, we identify four facies: 1) resistant cross-stratified facies, 2) smooth, fine-grained cross-stratified facies, 3) dark gray, pitted facies, and 4) recessive, vertically fractured facies. Panoramic Mastcam observations reveal facies distributions and associations, and show cross-bedded facies that are similar to those observed at the Rocknest and Bathurst_Inlet locations. MAHLI and RMI images are used to determine the grain size, sorting, rounding and sedimentary fabric of the different facies. High-resolution images also reveal small-scale diagenetic features and sedimentary structures that are used to reconstruct the depositional and diagenetic history.

Downscaling hydrodynamics features to depict causes of major productivity of Sicilian-Maltese area and implications for resource management.

PubMed

Capodici, Fulvio; Ciraolo, Giuseppe; Cosoli, Simone; Maltese, Antonino; Mangano, M Cristina; Sarà, Gianluca

2018-07-01

Chlorophyll-a (CHL-a) and sea surface temperature (SST) are generally accepted as proxies for water quality. They can be easily retrieved in a quasi-near real time mode through satellite remote sensing and, as such, they provide an overview of the water quality on a synoptic scale in open waters. Their distributions evolve in space and time in response to local and remote forcing, such as winds and currents, which however have much finer temporal and spatial scales than those resolvable by satellites in spite of recent advances in satellite remote-sensing techniques. Satellite data are often characterized by a moderate temporal resolution to adequately catch the actual sub-grid physical processes. Conventional pointwise measurements can resolve high-frequency motions such as tides or high-frequency wind-driven currents, however they are inadequate to resolve their spatial variability over wide areas. We show in this paper that a combined use of near-surface currents, available through High-Frequency (HF) radars, and satellite data (e.g., TERRA and AQUA/MODIS), can properly resolve the main oceanographic features in both coastal and open-sea regions, particularly at the coastal boundaries where satellite imageries fail, and are complementary tools to interpret ocean productivity and resource management in the Sicily Channel. Copyright © 2018. Published by Elsevier B.V.

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

Sarshar, Mohammad Amin; Swarctz, Christopher; Hunter, Scott Robert

In this paper, the iceophobic properties of superhydrophobic surfaces are investigated under dynamic flow conditions by using a closed loop low-temperature wind tunnel. Superhydrophobic surfaces were prepared by coating the substrates of aluminum and steel plates with nano-structured hydrophobic particles. The superhydrophobic plates along with uncoated control ones were exposed to an air flow of 12 m/s and 20 F accompanying micron-sized water droplets in the icing wind tunnel and the ice formation and accretion were probed by high-resolution CCD cameras. Results show that the superhydrophobic coatings significantly delay the ice formation and accretion even under the dynamic flow conditionmore » of the highly energetic impingement of accelerated super-cooled water droplets. It is found that there is a time scale for this phenomenon (delay of the ice formation) which has a clear correlation with the contact angle hysteresis and the length scale of surface roughness of the superhydrophobic surface samples, being the highest for the plate with the lowest contact angle hysteresis and finer surface roughness. The results suggest that the key parameter for designing iceophobic surfaces is to retain a low contact angle hysteresis (dynamic property) and the non-wetting superhydrophobic state under the hydrodynamic pressure of impinging droplets, rather than to only have a high contact angle (static property), in order to result in efficient anti-icing properties under dynamic conditions such as forced flows.« less

EnviroAtlas: Providing Nationwide Geospatial Ecosystem Goods and Services Indicators and Indices to Inform Decision-Making, Research, and Education

NASA Astrophysics Data System (ADS)

Neale, A. C.

2016-12-01

EnviroAtlas is a multi-organization effort led by the US Environmental Protection Agency to develop, host and display a large suite of nation-wide geospatial indicators and indices of ecosystem services. This open access tool allows users to view, analyze, and download a wealth of geospatial data and other resources related to ecosystem goods and services. More than 160 national indicators of ecosystem service supply, demand, and drivers of change provide a framework to inform decisions and policies at multiple spatial scales, educate a range of audiences, and supply data for research. A higher resolution component is also available, providing over 100 data layers for finer-scale analyses for selected communities across the US. The ecosystem goods and services data are organized into seven general ecosystem benefit categories: clean and plentiful water; natural hazard mitigation; food, fuel, and materials; climate stabilization; clean air; biodiversity conservation; and recreation, culture, and aesthetics. Each indicator is described in terms of how it is important to human health or well-being. EnviroAtlas includes data describing existing ecosystem markets for water quality and quantity, biodiversity, wetland mitigation, and carbon credits. This presentation will briefly describe the EnviroAtlas data and tools and how they are being developed and used in ongoing research studies and in decision-making contexts.

New, Improved Bulk-microphysical Schemes for Studying Precipitation Processes in WRF. Part 1; Comparisons with Other Schemes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shi, J.; Chen, S. S> ; Lang, S.; Hong, S.-Y.; Thompson, G.; Peters-Lidard, C.; Hou, A.; Braun, S.;

High-Resolution Radar Imagery of Mars

NASA Astrophysics Data System (ADS)

Harmon, John K.; Nolan, M. C.

2009-09-01

We present high-resolution radar images of Mars obtained during the 2005 and 2007 oppositions. The images were constructed from long-code delay-Doppler observations made with the Arecibo S-band (13-cm) radar. The average image resolution of 3 km represented a better than order-of-magnitude improvement over pre-upgrade Arecibo imagery of the planet. Images of depolarized reflectivity (an indicator primarily of wavelength-scale surface roughness) show the same bright volcanic flow features seen in earlier imagery, but with much finer detail. A new image of the Elysium region shows fine detail in the radar-bright channels of Athabasca Vallis, Marte Vallis, and Grjota Vallis. The new images of Tharsis and Olympus Mons also show a complex array of radar-bright and radar-dark features. Southern Amazonis exhibits some of the most complex and puzzling radar-bright structure on the planet. Another curiosity is the Chryse/Xanthe/Channels region, where we find some radar-bright features in or adjacent to fluvial chaos structures. Chryse/Xanthe is also the only region of Mars showing radar-bright craters (which are rare on Mars but common on the Moon and Mercury). We also obtained the first delay-Doppler image showing the enhanced backscatter from the residual south polar ice cap. In addition to the depolarized imagery, we were able to make the first delay-Doppler images of the circular polarization ratio (an important diagnostic for surface roughness texture). We find that vast areas of the radar-bright volcanic regions have polarization ratios close to unity. Such high ratios are rare for terrestrial lava flows and only seen for extremely blocky surfaces giving high levels of multiple scattering.

Uncertainty of future projections of species distributions in mountainous regions.

PubMed

Tang, Ying; Winkler, Julie A; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution.

Uncertainty of future projections of species distributions in mountainous regions

PubMed Central

Tang, Ying; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution. PMID:29320501

Three-dimensional fusion of spaceborne and ground radar reflectivity data using a neural network-based approach

NASA Astrophysics Data System (ADS)

Kou, Leilei; Wang, Zhuihui; Xu, Fen

2018-03-01

The spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission satellite (TRMM PR) can provide good measurement of the vertical structure of reflectivity, while ground radar (GR) has a relatively high horizontal resolution and greater sensitivity. Fusion of TRMM PR and GR reflectivity data may maximize the advantages from both instruments. In this paper, TRMM PR and GR reflectivity data are fused using a neural network (NN)-based approach. The main steps included are: quality control of TRMM PR and GR reflectivity data; spatiotemporal matchup; GR calibration bias correction; conversion of TRMM PR data from Ku to S band; fusion of TRMM PR and GR reflectivity data with an NN method; interpolation of reflectivity data that are below PR's sensitivity; blind areas compensation with a distance weighting-based merging approach; combination of three types of data: data with the NN method, data below PR's sensitivity and data within compensated blind areas. During the NN fusion step, the TRMM PR data are taken as targets of the training NNs, and gridded GR data after horizontal downsampling at different heights are used as the input. The trained NNs are then used to obtain 3D high-resolution reflectivity from the original GR gridded data. After 3D fusion of the TRMM PR and GR reflectivity data, a more complete and finer-scale 3D radar reflectivity dataset incorporating characteristics from both the TRMM PR and GR observations can be obtained. The fused reflectivity data are evaluated based on a convective precipitation event through comparison with the high resolution TRMM PR and GR data with an interpolation algorithm.

A demonstration of wetland vegetation mapping in Florida from computer-processed satellite and aircraft multispectral scanner data

NASA Technical Reports Server (NTRS)

Butera, M. K. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Major vegetative classes identified by the remote sensing technique were cypress swamp, pine, wetland grasses, salt grass, mixed mangrove, black mangrove, Brazilian pepper. Australian pine and melaleuca were not satisfactorily classified from LANDSAT. Aircraft scanners provided better resolution resulting in a classification of finer surface detail. An edge effect, created by the integration of diverse spectral responses within boundary elements of digital data, affected the wetlands classification. Accuracy classification for aircraft was 68% and for LANDSAT was 74%.

Microscale optical cryptography using a subdiffraction-limit optical key

NASA Astrophysics Data System (ADS)

Ogura, Yusuke; Aino, Masahiko; Tanida, Jun

2018-04-01

We present microscale optical cryptography using a subdiffraction-limit optical pattern, which is finer than the diffraction-limit size of the decrypting optical system, as a key and a substrate with a reflectance distribution as an encrypted image. Because of the subdiffraction-limit spatial coding, this method enables us to construct a secret image with the diffraction-limit resolution. Simulation and experimental results demonstrate, both qualitatively and quantitatively, that the secret image becomes recognizable when and only when the substrate is illuminated with the designed key pattern.

Piloted studies of Enhanced or Synthetic Vision display parameters

NASA Technical Reports Server (NTRS)

Harris, Randall L., Sr.; Parrish, Russell V.

1992-01-01

This paper summarizes the results of several studies conducted at Langley Research Center over the past few years. The purposes of these studies were to investigate parameters of pictorial displays and imaging sensors that affect pilot approach and landing performance. Pictorial displays have demonstrated exceptional tracking performance and improved the pilots' spatial awareness. Stereopsis cueing improved pilot flight performance and reduced pilot stress. Sensor image parameters such as increased field-of-view. faster image update rate, and aiding symbology improved flare initiation. Finer image resolution and magnification improved attitude control performance parameters.

Anterior-segment imaging for assessment of glaucoma

PubMed Central

Ursea, Roxana; Silverman, Ronald H

2010-01-01

This article summarizes the physics, technology and clinical application of ultrasound biomicroscopy (UBM) and optical coherence tomography (OCT) for assessment of the anterior segment in glaucoma. UBM systems use frequencies ranging from approximately 35 to 80 MHz, as compared with typical 10-MHz systems used for general-purpose ophthalmic imaging. OCT systems use low-coherence, near-infrared light to provide detailed images of anterior segment structures at resolutions exceeding that of UBM. Both technologies allow visualization of the iridocorneal angle and, thus, can contribute to the diagnosis and management of glaucoma. OCT systems are advantageous, being noncontact proceedures and providing finer resolution than UBM, but UBM systems are superior for the visualization of retroiridal structures, including the ciliary body, posterior chamber and zonules, which can provide crucial diagnostic information for the assessment of glaucoma. PMID:20305726

Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.

PubMed

Dornas, João V; Braun, Jochen

2018-01-15

Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Estimation of the atmosphere-ocean fluxes of greenhouse gases and aerosols at the finer resolution of the coastal ocean.

NASA Astrophysics Data System (ADS)

Vieira, Vasco; Sahlée, Erik; Jurus, Pavel; Clementi, Emanuela; Pettersson, Heidi; Mateus, Marcos

2016-04-01

The balances and fluxes of greenhouse gases and aerosols between atmosphere and ocean are fundamental for Earth's heat budget. Hence, the scientific community needs to know and simulate them with accuracy in order to monitor climate change from Earth-Observation satellites and to produce reliable estimates of climate change using Earth-System Models (ESM). So far, ESM have represented earth's surface with coarser resolutions so that each cell of the marine domain is dominated by the open ocean. In such case it is enough to use simple algorithms considering the wind speed 10m above sea-surface (u10) as sole driver of the gas transfer velocity. The formulation by Wanninkhof (1992) is broadly accepted as the best. However, the ESM community is becoming increasingly aware of the need to model with finer resolutions. Then, it is no longer enough to only consider u10 when modelling gas transfer velocities across the coastal oceans' surfaces. More comprehensive formulations are required that adjust better to local conditions by also accounting for the effects of sea-surface agitation, wave breaking, atmospheric stability of the Surface Boundary Layer, current drag with the bottom, surfactants and rain. Accurate algorithms are also fundamental to monitor atmosphere and ocean greenhouse gas concentrations using satellite data and reverse modelling. Past satellite missions ERS, Envisat, Jason-2, Aqua, Terra and Metop, have already been remotely sensing the ocean's surface at much finer resolutions than ESM using instruments like MERIS, MODIS, AMR, AATSR, MIPAS, Poseidon-3, SCIAMACHY, SeaWiFS, and IASI. The planned new satellite missions Sentinel-3, OCO-2 and GOSAT will further increase the resolutions. We developed a framework to congregate competing formulations for the estimation of the solubility and transfer velocity of virtually any gas on the biosphere taking into consideration the atmosphere and ocean fundamental variables and their derived geophysical processes mentioned above. First, we tested with measured data from the Baltic. Then, we adapted it to a coupler for atmosphere (WRF) and ocean (WW3-NEMO) model components and tested with simulated data relative to the Mediterranean and coastal North Atlantic. Computational speed was greatly improved by calculus vectorization and parallelization. The classical solubility formulation was compared to a recent alternative relying in a different chemistry background. Differences between solubility formulations resulted in a bias of 3.86×106 ton of CO2, 880.7 ton of CH4 and 401 ton of N2O dissolved in the first meter below the sea-surface of the modelled region, corresponding to 5.9% of the N2O yearly discharged by European estuaries. These differences concentrated in sensitive areas for Earth-System dynamics: the cooler polar waters and warmer less-saline coastal waters. The classical transfer velocity formulation using solely u10 was compared to alternatives using the friction velocity, atmospheric stability, sea-surface agitation and wave breaking. Differences between estimated transfer velocities concentrated at the coastal ocean and resulted in 55.82% of the gas volume transferred over the sea-surface of the modelled region during the 66h simulated period.

Land use regression models to assess air pollution exposure in Mexico City using finer spatial and temporal input parameters.

PubMed

Son, Yeongkwon; Osornio-Vargas, Álvaro R; O'Neill, Marie S; Hystad, Perry; Texcalac-Sangrador, José L; Ohman-Strickland, Pamela; Meng, Qingyu; Schwander, Stephan

2018-05-17

The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM 2.5 , PM 10 , O 3 , NO 2 , CO and SO 2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO). Hourly traffic density was included as a temporal variable besides meteorological and holiday variables. Models of hourly, daily, monthly, 6-monthly and annual averages were developed and evaluated using traditional and novel indices. The developed spatiotemporal LUR models yielded predicted concentrations with good spatial and temporal agreements with measured pollutant levels except for the hourly PM 2.5 , PM 10 and SO 2 . Most of the LUR models met performance goals based on the standardized indices. LUR models with temporal scales greater than one hour were successfully developed using mixed effect models with LASSO and showed superior model performance compared to earlier LUR models, especially for time scales of a day or longer. The newly developed LUR models will be further refined with ongoing Mexico City air pollution sampling campaigns to improve personal exposure assessments. Copyright © 2018. Published by Elsevier B.V.

Simulation of the Atmospheric Boundary Layer for Wind Energy Applications

NASA Astrophysics Data System (ADS)

Marjanovic, Nikola

Energy production from wind is an increasingly important component of overall global power generation, and will likely continue to gain an even greater share of electricity production as world governments attempt to mitigate climate change and wind energy production costs decrease. Wind energy generation depends on wind speed, which is greatly influenced by local and synoptic environmental forcings. Synoptic forcing, such as a cold frontal passage, exists on a large spatial scale while local forcing manifests itself on a much smaller scale and could result from topographic effects or land-surface heat fluxes. Synoptic forcing, if strong enough, may suppress the effects of generally weaker local forcing. At the even smaller scale of a wind farm, upstream turbines generate wakes that decrease the wind speed and increase the atmospheric turbulence at the downwind turbines, thereby reducing power production and increasing fatigue loading that may damage turbine components, respectively. Simulation of atmospheric processes that span a considerable range of spatial and temporal scales is essential to improve wind energy forecasting, wind turbine siting, turbine maintenance scheduling, and wind turbine design. Mesoscale atmospheric models predict atmospheric conditions using observed data, for a wide range of meteorological applications across scales from thousands of kilometers to hundreds of meters. Mesoscale models include parameterizations for the major atmospheric physical processes that modulate wind speed and turbulence dynamics, such as cloud evolution and surface-atmosphere interactions. The Weather Research and Forecasting (WRF) model is used in this dissertation to investigate the effects of model parameters on wind energy forecasting. WRF is used for case study simulations at two West Coast North American wind farms, one with simple and one with complex terrain, during both synoptically and locally-driven weather events. The model's performance with different grid nesting configurations, turbulence closures, and grid resolutions is evaluated by comparison to observation data. Improvement to simulation results from the use of more computationally expensive high resolution simulations is only found for the complex terrain simulation during the locally-driven event. Physical parameters, such as soil moisture, have a large effect on locally-forced events, and prognostic turbulence kinetic energy (TKE) schemes are found to perform better than non-local eddy viscosity turbulence closure schemes. Mesoscale models, however, do not resolve turbulence directly, which is important at finer grid resolutions capable of resolving wind turbine components and their interactions with atmospheric turbulence. Large-eddy simulation (LES) is a numerical approach that resolves the largest scales of turbulence directly by separating large-scale, energetically important eddies from smaller scales with the application of a spatial filter. LES allows higher fidelity representation of the wind speed and turbulence intensity at the scale of a wind turbine which parameterizations have difficulty representing. Use of high-resolution LES enables the implementation of more sophisticated wind turbine parameterizations to create a robust model for wind energy applications using grid spacing small enough to resolve individual elements of a turbine such as its rotor blades or rotation area. Generalized actuator disk (GAD) and line (GAL) parameterizations are integrated into WRF to complement its real-world weather modeling capabilities and better represent wind turbine airflow interactions, including wake effects. The GAD parameterization represents the wind turbine as a two-dimensional disk resulting from the rotation of the turbine blades. Forces on the atmosphere are computed along each blade and distributed over rotating, annular rings intersecting the disk. While typical LES resolution (10-20 m) is normally sufficient to resolve the GAD, the GAL parameterization requires significantly higher resolution (1-3 m) as it does not distribute the forces from the blades over annular elements, but applies them along lines representing individual blades. In this dissertation, the GAL is implemented into WRF and evaluated against the GAD parameterization from two field campaigns that measured the inflow and near-wake regions of a single turbine. The data-sets are chosen to allow validation under the weakly convective and weakly stable conditions characterizing most turbine operations. The parameterizations are evaluated with respect to their ability to represent wake wind speed, variance, and vorticity by comparing fine-resolution GAD and GAL simulations along with coarse-resolution GAD simulations. Coarse-resolution GAD simulations produce aggregated wake characteristics similar to both GAD and GAL simulations (saving on computational cost), while the GAL parameterization enables resolution of near wake physics (such as vorticity shedding and wake expansion) for high fidelity applications. (Abstract shortened by ProQuest.).

LES on unstructured deforming meshes: Towards reciprocating IC engines

NASA Technical Reports Server (NTRS)

Haworth, D. C.; Jansen, K.

1996-01-01

A variable explicit/implicit characteristics-based advection scheme that is second-order accurate in space and time has been developed recently for unstructured deforming meshes (O'Rourke & Sahota 1996a). To explore the suitability of this methodology for Large-Eddy Simulation (LES), three subgrid-scale turbulence models have been implemented in the CHAD CFD code (O'Rourke & Sahota 1996b): a constant-coefficient Smagorinsky model, a dynamic Smagorinsky model for flows having one or more directions of statistical homogeneity, and a Lagrangian dynamic Smagorinsky model for flows having no spatial or temporal homogeneity (Meneveau et al. 1996). Computations have been made for three canonical flows, progressing towards the intended application of in-cylinder flow in a reciprocating engine. Grid sizes were selected to be comparable to the coarsest meshes used in earlier spectral LES studies. Quantitative results are reported for decaying homogeneous isotropic turbulence, and for a planar channel flow. Computations are compared to experimental measurements, to Direct-Numerical Simulation (DNS) data, and to Rapid-Distortion Theory (RDT) where appropriate. Generally satisfactory evolution of first and second moments is found on these coarse meshes; deviations are attributed to insufficient mesh resolution. Issues include mesh resolution and computational requirements for a specified level of accuracy, analytic characterization of the filtering implied by the numerical method, wall treatment, and inflow boundary conditions. To resolve these issues, finer-mesh simulations and computations of a simplified axisymmetric reciprocating piston-cylinder assembly are in progress.

The role of country-to-region assignments in global integrated modeling of energy, agriculture, land use, and climate

NASA Astrophysics Data System (ADS)

Kyle, P.; Patel, P.; Calvin, K. V.

2014-12-01

Global integrated assessment models used for understanding the linkages between the future energy, agriculture, and climate systems typically represent between 8 and 30 geopolitical macro-regions, balancing the benefits of geographic resolution with the costs of additional data collection, processing, analysis, and computing resources. As these models are continually being improved and updated in order to address new questions for the research and policy communities, it is worth examining the consequences of the country-to-region mapping schemes used for model results. This study presents an application of a data processing system built for the GCAM integrated assessment model that allows any country-to-region assignments, with a minimum of four geopolitical regions and a maximum of 185. We test ten different mapping schemes, including the specific mappings used in existing major integrated assessment models. We also explore the impacts of clustering nations into regions according to the similarity of the structure of each nation's energy and agricultural sectors, as indicated by multivariate analysis. Scenarios examined include a reference scenario, a low-emissions scenario, and scenarios with agricultural and buildings sector climate change impacts. We find that at the global level, the major output variables (primary energy, agricultural land use) are surprisingly similar regardless of regional assignments, but at finer geographic scales, differences are pronounced. We suggest that enhancing geographic resolution is advantageous for analysis of climate impacts on the buildings and agricultural sectors, due to the spatial heterogeneity of these drivers.

Satellite based assessment of recent permafrost extent and active layer trends over Alaska and Northwest Canada

NASA Astrophysics Data System (ADS)

Kim, Y.; Kimball, J. S.; PARK, H.; Yi, Y.

2017-12-01

Climate change in the Boreal-Arctic region has experienced greater surface air temperature (SAT) warming than the global average in recent decades, which is promoting permafrost thawing and active layer deepening. Permafrost extent (PE) and active layer thickness (ALT) are key environmental indicators of recent climate change, and strongly impact other eco-hydrological processes including land-atmosphere carbon exchange. We developed a new approach for regional estimation and monitoring of PE using daily landscape freeze-thaw (FT) records derived from satellite microwave (37 GHz) brightness temperature (Tb) observations. ALT was estimated within the PE domain using empirical modeling of land cover dependent edaphic factors and an annual thawing index derived from MODIS land surface temperature (LST) observations and reanalysis based surface air temperatures (SAT). The PE and ALT estimates were derived over the 1980-2016 satellite record and NASA ABoVE (Arctic Boreal Vulnerability Experiment) domain encompassing Alaska and Northwest Canada. The baseline model estimates were derived at 25-km resolution consistent with the satellite FT global record. Our results show recent widespread PE decline and deepening ALT trends, with larger spatial variability and model uncertainty along the southern PE boundary. Larger PE and ALT variability occurs over heterogeneous permafrost subzones characterized by dense vegetation, and variable snow cover and organic layer conditions. We also tested alternative PE and ALT estimates derived using finer (6-km) scale satellite Tb (36.5 GHz) and FT retrievals from a calibrated AMSR-E and AMSR2 sensor record. The PE and ALT results were compared against other independent observations, including process model simulations, in situ measurements, and permafrost inventory records. A model sensitivity analysis was conducted to evaluate snow cover, soil organic layer, and vegetation composition impacts to ALT. The finer delineation of permafrost and active layer conditions provides enhanced regional monitoring of PE and ALT changes over the ABoVE domain, including heterogeneous permafrost subzones.

Atmospheric blocking in the Climate SPHINX simulations: the role of orography and resolution

NASA Astrophysics Data System (ADS)

Davini, Paolo; Corti, Susanna; D'Andrea, Fabio; Riviere, Gwendal; von Hardenberg, Jost

2017-04-01

The representation of atmospheric blocking in numerical simulations, especially over the Euro-Atlantic region, still represents a main concern for the climate modelling community. We here discuss the Northern Hemisphere winter atmospheric blocking representation in a set of 30-year simulations which has been performed in the framework of the PRACE project "Climate SPHINX". Simulations were run using the EC-Earth Global Climate Model with several ensemble members at 5 different horizontal resolutions (ranging from 125 km to 16 km). Results show that the negative bias in blocking frequency over Europe becomes negligible at resolutions of about 40 km and finer. However, the blocking duration is still underestimated by 1-2 days, suggesting that the correct blocking frequencies are achieved with an overestimation of the number of blocking onsets. The reasons leading to such improvements are then discussed, highlighting the role of orography in shaping the Atlantic jet stream: at higher resolution the jet is weaker and less penetrating over Europe, favoring the breaking of synoptic Rossby waves over the Atlantic stationary ridge and thus increasing the simulated blocking frequency.

Decadal Variability of Temperature and Salinity in the Northwest Atlantic Ocean

NASA Astrophysics Data System (ADS)

Mishonov, A. V.; Seidov, D.; Reagan, J. R.; Boyer, T.; Parsons, A. R.

2017-12-01

There are only a few regions in the World Ocean where the density of observations collected over the past 60 years is sufficient for reliable data mapping with spatial resolutions finer than one-degree. The Northwest Atlantic basin is one such regions where a spatial resolution of gridded temperature and salinity fields, comparable to those generated by eddy-resolving numerical models of ocean circulation, has recently becomes available. Using the new high-resolution Northwest Atlantic Regional Climatology, built on quarter-degree and one-tenth-degree resolution fields, we analyzed decadal variability and trends of temperature and salinity over 60 years in the Northwest Atlantic, and two 30-year ocean climates of 1955-1984 and 1985-2012 to evaluate the oceanic climate shift in this region. The 30-year climate shift is demonstrated using an innovative 3-D visualization of temperature and salinity. Spatial and temporal variability of heat accumulation found in previous research of the entire North Atlantic Ocean persists in the Northwest Atlantic Ocean. Salinity changes between two 30-year climates were also computed and are discussed.

X-Ray Diffractive Optics

NASA Technical Reports Server (NTRS)

Dennis, Brian; Li, Mary; Skinner, Gerald

2013-01-01

X-ray optics were fabricated with the capability of imaging solar x-ray sources with better than 0.1 arcsecond angular resolution, over an order of magnitude finer than is currently possible. Such images would provide a new window into the little-understood energy release and particle acceleration regions in solar flares. They constitute one of the most promising ways to probe these regions in the solar atmosphere with the sensitivity and angular resolution needed to better understand the physical processes involved. A circular slit structure with widths as fine as 0.85 micron etched in a silicon wafer 8 microns thick forms a phase zone plate version of a Fresnel lens capable of focusing approx. =.6 keV x-rays. The focal length of the 3-cm diameter lenses is 100 microns, and the angular resolution capability is better than 0.1 arcsecond. Such phase zone plates were fabricated in Goddard fs Detector Development Lab. (DDL) and tested at the Goddard 600-microns x-ray test facility. The test data verified that the desired angular resolution and throughput efficiency were achieved.

Beyond scenario planning: projecting the future using models at Wind Cave National Park (USA)

NASA Astrophysics Data System (ADS)

King, D. A.; Bachelet, D. M.; Symstad, A. J.

2011-12-01

Scenario planning has been used by the National Park Service as a tool for natural resource management planning in the face of climate change. Sets of plausible but divergent future scenarios are constructed from available information and expert opinion and serve as starting point to derive climate-smart management strategies. However, qualitative hypotheses about how systems would react to a particular set of conditions assumed from coarse scale climate projections may lack the scientific rigor expected from a federal agency. In an effort to better assess the range of likely futures at Wind Cave National Park, a project was conceived to 1) generate high resolution historic and future climate time series to identify local weather patterns that may or may not persist, 2) simulate the hydrological cycle in this geologically varied landscape and its response to future climate, 3) project vegetation dynamics and ensuing changes in the biogeochemical cycles given grazing and fire disturbances under new climate conditions, and 4) synthesize and compare results with those from the scenario planning exercise. In this framework, we tested a dynamic global vegetation model against local information on vegetation cover, disturbance history and stream flow to better understand the potential resilience of these ecosystems to climate change. We discuss the tradeoffs between a coarse scale application of the model showing regional trends with limited ability to project the fine scale mosaic of vegetation at Wind Cave, and a finer scale approach that can account for local slope effects on water balance and better assess the vulnerability of landscape facets, but requires more intensive data acquisition. We elaborate on the potential for sharing information between models to mitigate the often-limited treatment of biological feedbacks in the physical representations of soil and atmospheric processes.

Water Balance in the Amazon Basin from a Land Surface Model Ensemble

NASA Technical Reports Server (NTRS)

Getirana, Augusto C. V.; Dutra, Emanuel; Guimberteau, Matthieu; Kam, Jonghun; Li, Hong-Yi; Decharme, Bertrand; Zhang, Zhengqiu; Ducharne, Agnes; Boone, Aaron; Balsamo, Gianpaolo;

Simulating Non-Fickian Transport across Péclet Regimes by doing Lévy Flights in the Rank Space of Velocity

NASA Astrophysics Data System (ADS)

Most, S.; Dentz, M.; Bolster, D.; Bijeljic, B.; Nowak, W.

2017-12-01

Transport in real porous media shows non-Fickian characteristics. In the Lagrangian perspective this leads to skewed distributions of particle arrival times. The skewness is triggered by particles' memory of velocity that persists over a characteristic length. Capturing process memory is essential to represent non-Fickianity thoroughly. Classical non-Fickian models (e.g., CTRW models) simulate the effects of memory but not the mechanisms leading to process memory. CTRWs have been applied successfully in many studies but nonetheless they have drawbacks. In classical CTRWs each particle makes a spatial transition for which each particle adapts a random transit time. Consecutive transit times are drawn independently from each other, and this is only valid for sufficiently large spatial transitions. If we want to apply a finer numerical resolution than that, we have to implement memory into the simulation. Recent CTRW methods use transitions matrices to simulate correlated transit times. However, deriving such transition matrices require transport data of a fine-scale transport simulation, and the obtained transition matrix is solely valid for this single Péclet regime. The CTRW method we propose overcomes all three drawbacks: 1) We simulate transport without restrictions in transition length. 2) We parameterize our CTRW without requiring a transport simulation. 3) Our parameterization scales across Péclet regimes. We do so by sampling the pore-scale velocity distribution to generate correlated transit times as a Lévy flight on the CDF-axis of velocities with reflection at 0 and 1. The Lévy flight is parametrized only by the correlation length. We explicitly model memory including the evolution and decay of non-Fickianity, so it extends from local via pre-asymptotic to asymptotic scales.

Diversity and distribution of deep-sea shrimps in the Ross Sea region of Antarctica.

PubMed

Basher, Zeenatul; Bowden, David A; Costello, Mark J

2014-01-01

Although decapod crustaceans are widespread in the oceans, only Natantia (shrimps) are common in the Antarctic. Because remoteness, depth and ice cover restrict sampling in the South Ocean, species distribution modelling is a useful tool for evaluating distributions. We used physical specimen and towed camera data to describe the diversity and distribution of shrimps in the Ross Sea region of Antarctica. Eight shrimp species were recorded: Chorismus antarcticus; Notocrangon antarcticus; Nematocarcinus lanceopes; Dendrobranchiata; Pasiphaea scotiae; Pasiphaea cf. ledoyeri; Petalidium sp., and a new species of Lebbeus. For the two most common species, N. antarcticus and N. lanceopes, we used maximum entropy modelling, based on records of 60 specimens and over 1130 observations across 23 sites in depths from 269 m to 3433 m, to predict distributions in relation to environmental variables. Two independent sets of environmental data layers at 0.05° and 0.5° resolution respectively, showed how spatial resolution affected the model. Chorismus antarcticus and N. antarcticus were found only on the continental shelf and upper slopes, while N. lanceopes, Lebbeus n. sp., Dendrobranchiata, Petalidium sp., Pasiphaea cf. ledoyeri, and Pasiphaea scotiae were found on the slopes, seamounts and abyssal plain. The environmental variables that contributed most to models for N. antarcticus were depth, chlorophyll-a concentration, temperature, and salinity, and for N. lanceopes were depth, ice concentration, seabed slope/rugosity, and temperature. The relative ranking, but not the composition of these variables changed in models using different spatial resolutions, and the predicted extent of suitable habitat was smaller in models using the finer-scale environmental layers. Our modelling indicated that shrimps were widespread throughout the Ross Sea region and were thus likely to play important functional role in the ecosystem, and that the spatial resolution of data needs to be considered both in the use of species distribution models.

Diversity and Distribution of Deep-Sea Shrimps in the Ross Sea Region of Antarctica

PubMed Central

Basher, Zeenatul; Bowden, David A.; Costello, Mark J.

2014-01-01

Although decapod crustaceans are widespread in the oceans, only Natantia (shrimps) are common in the Antarctic. Because remoteness, depth and ice cover restrict sampling in the South Ocean, species distribution modelling is a useful tool for evaluating distributions. We used physical specimen and towed camera data to describe the diversity and distribution of shrimps in the Ross Sea region of Antarctica. Eight shrimp species were recorded: Chorismus antarcticus; Notocrangon antarcticus; Nematocarcinus lanceopes; Dendrobranchiata; Pasiphaea scotiae; Pasiphaea cf. ledoyeri; Petalidium sp., and a new species of Lebbeus. For the two most common species, N. antarcticus and N. lanceopes, we used maximum entropy modelling, based on records of 60 specimens and over 1130 observations across 23 sites in depths from 269 m to 3433 m, to predict distributions in relation to environmental variables. Two independent sets of environmental data layers at 0.05° and 0.5° resolution respectively, showed how spatial resolution affected the model. Chorismus antarcticus and N. antarcticus were found only on the continental shelf and upper slopes, while N. lanceopes, Lebbeus n. sp., Dendrobranchiata, Petalidium sp., Pasiphaea cf. ledoyeri, and Pasiphaea scotiae were found on the slopes, seamounts and abyssal plain. The environmental variables that contributed most to models for N. antarcticus were depth, chlorophyll-a concentration, temperature, and salinity, and for N. lanceopes were depth, ice concentration, seabed slope/rugosity, and temperature. The relative ranking, but not the composition of these variables changed in models using different spatial resolutions, and the predicted extent of suitable habitat was smaller in models using the finer-scale environmental layers. Our modelling indicated that shrimps were widespread throughout the Ross Sea region and were thus likely to play important functional role in the ecosystem, and that the spatial resolution of data needs to be considered both in the use of species distribution models. PMID:25051333

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

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.

Quantifying Diurnal and Spatial Variations in CO2 Concentrations and Partial Columns using High-Resolution Global Model Simulations

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.

A gain-loss framework based on ensemble flow forecasts to switch the urban drainage-wastewater system management towards energy optimization during dry periods

NASA Astrophysics Data System (ADS)

Courdent, Vianney; Grum, Morten; Munk-Nielsen, Thomas; Mikkelsen, Peter S.

2017-05-01

Precipitation is the cause of major perturbation to the flow in urban drainage and wastewater systems. Flow forecasts, generated by coupling rainfall predictions with a hydrologic runoff model, can potentially be used to optimize the operation of integrated urban drainage-wastewater systems (IUDWSs) during both wet and dry weather periods. Numerical weather prediction (NWP) models have significantly improved in recent years, having increased their spatial and temporal resolution. Finer resolution NWP are suitable for urban-catchment-scale applications, providing longer lead time than radar extrapolation. However, forecasts are inevitably uncertain, and fine resolution is especially challenging for NWP. This uncertainty is commonly addressed in meteorology with ensemble prediction systems (EPSs). Handling uncertainty is challenging for decision makers and hence tools are necessary to provide insight on ensemble forecast usage and to support the rationality of decisions (i.e. forecasts are uncertain and therefore errors will be made; decision makers need tools to justify their choices, demonstrating that these choices are beneficial in the long run). This study presents an economic framework to support the decision-making process by providing information on when acting on the forecast is beneficial and how to handle the EPS. The relative economic value (REV) approach associates economic values with the potential outcomes and determines the preferential use of the EPS forecast. The envelope curve of the REV diagram combines the results from each probability forecast to provide the highest relative economic value for a given gain-loss ratio. This approach is traditionally used at larger scales to assess mitigation measures for adverse events (i.e. the actions are taken when events are forecast). The specificity of this study is to optimize the energy consumption in IUDWS during low-flow periods by exploiting the electrical smart grid market (i.e. the actions are taken when no events are forecast). Furthermore, the results demonstrate the benefit of NWP neighbourhood post-processing methods to enhance the forecast skill and increase the range of beneficial uses.

Thermophysical Variation within Dune Fields in the Southern Hemisphere of Mars

NASA Astrophysics Data System (ADS)

Courville, S. W.; Putzig, N. E.; Hoover, R.; Fenton, L. K.

2016-12-01

The activity and composition of Martian sand dunes, which are relatively young features, provide insight into the current and recent climate state of Mars. This study investigates small-scale variations of thermophysical properties within dune fields across the southern hemisphere of Mars to better understand near-surface composition. Previous morphological studies of southern hemisphere dune fields on Mars indicate a trend of decreasing activity with increasing latitude. We observe a corresponding trend in thermal properties. To investigate the thermal behavior of the dunes, we use apparent thermal inertia (ATI) derived from the Mars Odyssey's Thermal Emission Imaging System (THEMIS), which has a resolution of 100 meters per pixel. Overlaying THEMIS ATI values on images and digital terrain models from the High Resolution Imaging Science Experiment (HiRISE) allows us to compare ATI with small-scale dune morphology and slopes. In general, we observe three types of ATI behavior: (1) fields with exposed ground between dunes display lower ATI on the dunes themselves, consistent with dunes of relatively low thermal inertia resting upon a wind-resistant consolidated bed with higher thermal inertia; (2) fields with little or no inter-dune exposures exhibit ATI in dune troughs that is 100 tiu or more lower than along crests, counterintuitively suggesting that dune trough material is finer than that along dune crests; and (3) fields with highly degraded dunes typically display uniform ATI values, indicating that their properties do not vary laterally at the resolution of THEMIS images or vertically within a seasonal skin depth. These ATI behaviors correspond to the activity state of the dune field with type 1 being the most active and occurring toward the equator, while type 3 is the least active and found mostly at high southern latitudes. To consider alternative explanations for the ATI variation observed in Type 2 fields, we created thermal models of slopes, lateral mixtures of two particle sizes, and layering of two particle sizes. However, these models are unable to explain the observed ATI, suggesting that the composition and/or activity of these dunes are more complicated than allowed by two-component models.

Towards high-resolution mantle convection simulations

NASA Astrophysics Data System (ADS)

Höink, T.; Richards, M. A.; Lenardic, A.

2009-12-01

The motion of tectonic plates at the Earth’s surface, earthquakes, most forms of volcanism, the growth and evolution of continents, and the volatile fluxes that govern the composition and evolution of the oceans and atmosphere are all controlled by the process of solid-state thermal convection in the Earth’s rocky mantle, with perhaps a minor contribution from convection in the iron core. Similar processes govern the evolution of other planetary objects such as Mars, Venus, Titan, and Europa, all of which might conceivably shed light on the origin and evolution of life on Earth. Modeling and understanding this complicated dynamical system is one of the true “grand challenges” of Earth and planetary science. In the past three decades much progress towards understanding the dynamics of mantle convection has been made, with the increasing aid of computational modeling. Numerical sophistication has evolved significantly, and a small number of independent codes have been successfully employed. Computational power continues to increase dramatically, and with it the ability to resolve increasingly finer fluid mechanical structures. Yet, the perhaps most often cited limitation in numerical modeling based publications is still the limitation of computing power, because the ability to resolve thermal boundary layers within the convecting mantle (e.g., lithospheric plates), requires a spatial resolution of ~ 10 km. At present, the largest supercomputing facilities still barely approach the power to resolve this length scale in mantle convection simulations that include the physics necessary to model plate-like behavior. Our goal is to use supercomputing facilities to perform 3D spherical mantle convection simulations that include the ingredients for plate-like behavior, i.e. strongly temperature- and stress-dependent viscosity, at Earth-like convective vigor with a global resolution of order 10 km. In order to qualify to use such facilities, it is also necessary to demonstrate good parallel efficiency. Here we will present two kinds of results: (1) scaling properties of the community code CitcomS on DOE/NERSC's supercomputer Franklin for up to ~ 6000 processors, and (2) preliminary simulations that illustrate the role of a low-viscosity asthenosphere in plate-like behavior in mantle convection.

Analysis and numerical study of inertia-gravity waves generated by convection in the tropics

NASA Astrophysics Data System (ADS)

Evan, Stephanie

2011-12-01

Gravity waves transport momentum and energy upward from the troposphere and by dissipation affect the large-scale structure of the middle atmosphere. An accurate representation of these waves in climate models is important for climate studies, but is still a challenge for most global and climate models. In the tropics, several studies have shown that mesoscale gravity waves and intermediate scale inertia-gravity waves play an important role in the dynamics of the upper atmosphere. Despite observational evidence for the importance of forcing of the tropical circulation by inertia-gravity waves, their exact properties and forcing of the tropical stratospheric circulation are not fully understood. In this thesis, properties of tropical inertia-gravity waves are investigated using radiosonde data from the 2006 Tropical Warm Pool International Cloud Experiment (TWP-ICE), the European Centre for Medium-Range Weather Forecasts (ECMWF) dataset and high-resolution numerical experiments. Few studies have characterized inertia-gravity wave properties using radiosonde profiles collected on a campaign basis. We first examine the properties of intermediate-scale inertia-gravity waves observed during the 2006 TWP-ICE campaign in Australia. We show that the total vertical flux of horizontal momentum associated with the waves is of the same order of magnitude as previous observations of Kelvin waves. This constitutes evidence for the importance of the forcing of the tropical circulation by intermediate-scale inertia-gravity waves. Then, we focus on the representation of inertia-gravity waves in analysis data. The wave event observed during TWP-ICE is also present in the ECMWF data. A comparison between the characteristics of the inertia-gravity wave derived with the ECMWF data to the properties of the wave derived with the radiosonde data shows that the ECMWF data capture similar structure for this wave event but with a larger vertical wavelength. The Weather Research and Forecasting (WRF) modeling system is used to understand the representation of the wave event in the ECMWF data. The model is configured as a tropical channel with a high top at 1 hPa. WRF is used with the same horizontal resolution (˜ 40 km) as the operational ECMWF in 2006 while using a finer vertical grid-spacing than ECMWF. Different experiments are performed to determine the sensitivity of the wave structure to cumulus schemes, initial conditions and vertical resolution. We demonstrate that high vertical resolution would be required for ECMWF to accurately resolve the vertical structure of inertia-gravity waves and their effect on the middle atmosphere circulation. Lastly we perform WRF simulations in January 2006 and 2007 to assess gravity wave forcing of the tropical stratospheric circulation. In these simulations a large part of the gravity wave spectrum is explicitly simulated. The WRF model is able to reproduce the evolution of the mean tropical stratospheric zonal wind when compared to observational data and the ECMWF reanalysis. It is shown that gravity waves account for 60% up to 80% of the total wave forcing of the tropical stratospheric circulation. We also compute wave forcing associated with intermediate-scale inertiagravity waves. In the WRF simulations this wave type represents ˜ 30% of the total gravity wave forcing. This suggests that intermediate-scale inertia-gravity waves can play an important role in the tropical middle-atmospheric circulation. In addition, the WRF high-resolution simulations are used to provide some guidance for constraining gravity wave parameterizations in coarse-grid climate models.

Evaluation and Intercomparison of MODIS and GEOV1 Global Leaf Area Index Products over Four Sites in North China

PubMed Central

Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping

2015-01-01

This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011–2013. The Terra + Aqua MODIS and Terra MODIS LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and intercompared using LAI reference maps to assess their uncertainty and seasonal variability The results showed that GEOV1 LAI is the most similar product with the LAI reference maps (R2 = 0.78 and RMSE = 0.59). The MODIS products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + Aqua MODIS (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra MODIS (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both MODIS and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than MODIS. MODIS anomalies mainly occurred during summer and likely occurred because of surface reflectance uncertainty, shorter temporal resolutions and inconsistency between simulated and MODIS surface reflectances. This study suggests that further improvements of the MODIS LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of MODIS observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509

On the surface roughness of a braidplain in an Alpine proglacial area

NASA Astrophysics Data System (ADS)

Baewert, H.; Morche, D.; Culha, C.

2014-12-01

Surface roughness is a crucial parameter of studies concerning (paleo) flood peak discharge estimation and related factors (cf. stream power). Usually, the analysis requires preliminary knowledge of grain size distribution of the study site. However, in some cases this is impractical, especially when investigating large areas, or even impossible due to inaccessibility. In addition, the particles in the channel are usually hidden by other particles or incorporated into finer sediment. Therefore, removing particles from the channel bottom is not suitable, because it falsifies the results. Here, the application of noninvasive terrestrial laser scanning (TLS) offers new possibilities. The indirect recording of the surface leads to a significant reduction of the workload. Furthermore, form roughness and burial/imbrication are taken into account. However, there are some disadvantages in using TLS. The resolution of the TLS data is a limiting factor when defining surface roughness, because coarseness at finer detail will not be captured at lower resolution (Baewert et al. 2014). There are numerous other factors, which may alter the results. We would like to further understand how the noise associated with TLS data alters the outcome and whether the interpolation method has an influence. This study focuses on the latter two issues. For this purpose, a braidplain in the forefield of the glacier Gepatschferner in Austria was surveyed using a terrestrial laser scanner. The images were taken from different angles and with different resolutions. Subsequently, the outliers are removed from the point cloud in order to investigate the influence of the noise. Thinning the point cloud is another method used to understand the effects of the point density. References Baewert, H., Bimböse, M., Bryk, A., Rascher, E., Schmidt, K.-H. & Morche, D. (2014): Roughness determination of coarse grained alpine river bed surfaces using Terrestrial Laser Scanning data. - Zeitschrift für Geomorphologie N.F. 58(1): 81-95. Doi: 10.1127/0372-8854/2013/S-00127 .

A novel multiscale topo-morphometric approach for separating arteries and veins via pulmonary CT imaging

NASA Astrophysics Data System (ADS)

Saha, Punam K.; Gao, Zhiyun; Alford, Sara; Sonka, Milan; Hoffman, Eric

2009-02-01

Distinguishing arterial and venous trees in pulmonary multiple-detector X-ray computed tomography (MDCT) images (contrast-enhanced or unenhanced) is a critical first step in the quantification of vascular geometry for purposes of determining, for instance, pulmonary hypertension, using vascular dimensions as a comparator for assessment of airway size, detection of pulmonary emboli and more. Here, a novel method is reported for separating arteries and veins in MDCT pulmonary images. Arteries and veins are modeled as two iso-intensity objects closely entwined with each other at different locations at various scales. The method starts with two sets of seeds -- one for arteries and another for veins. Initialized with seeds, arteries and veins grow iteratively while maintaining their spatial separation and eventually forming two disjoint objects at convergence. The method combines fuzzy distance transform, a morphologic feature, with a topologic connectivity property to iteratively separate finer and finer details starting at a large scale and progressing towards smaller scales. The method has been validated in mathematically generated tubular objects with different levels of fuzziness, scale and noise. Also, it has been successfully applied to clinical CT pulmonary data. The accuracy of the method has been quantitatively evaluated by comparing its results with manual outlining. For arteries, the method has yielded correctness of 81.7% at the cost of 6.7% false positives and 11.6% false negatives. Our method is very promising for automated separation of arteries and veins in MDCT pulmonary images even when there is no mark of intensity variation at conjoining locations.

Spatial relationships of levees and wetland systems within floodplains of the Wabash Basin, USA

NASA Astrophysics Data System (ADS)

Bray, E. N.; Morrison, R. R.; Nardi, F.; Annis, A.; Dong, Q.

2017-12-01

Given the unique biogeochemical, physical, and hydrologic services provided by floodplain wetlands, proper management of river systems should include an understanding of how floodplain modifications influences wetland ecosystems. The construction of levees can reduce river-floodplain connectivity, yet it is unclear how levees affect wetlands within a river system, let alone the cumulative impacts within an entire watershed. This paper explores spatial relationships between levee and floodplain wetland systems in the Wabash basin, United States. We used a hydrogeomorphic floodplain delineation technique to map floodplain extents and identify wetlands that may be hydrologically connected to river networks. We then spatially examined the relationship between levee presence, wetland area, and other river network attributes within discrete HUC-12 sub-basins. Our results show that cumulative wetland area is relatively constant in sub-basins that contain levees, regardless of maximum stream order within the sub-basin. In sub-basins that do not contain levees, cumulative wetland area increases with maximum stream order. However, we found that wetland distributions around levees can be complex, and further studies on the influence of levees on wetland habitat may need to be evaluated at finer-resolution spatial scales.

New algorithms for field-theoretic block copolymer simulations: Progress on using adaptive-mesh refinement and sparse matrix solvers in SCFT calculations

NASA Astrophysics Data System (ADS)

Sides, Scott; Jamroz, Ben; Crockett, Robert; Pletzer, Alexander

2012-02-01

Self-consistent field theory (SCFT) for dense polymer melts has been highly successful in describing complex morphologies in block copolymers. Field-theoretic simulations such as these are able to access large length and time scales that are difficult or impossible for particle-based simulations such as molecular dynamics. The modified diffusion equations that arise as a consequence of the coarse-graining procedure in the SCF theory can be efficiently solved with a pseudo-spectral (PS) method that uses fast-Fourier transforms on uniform Cartesian grids. However, PS methods can be difficult to apply in many block copolymer SCFT simulations (eg. confinement, interface adsorption) in which small spatial regions might require finer resolution than most of the simulation grid. Progress on using new solver algorithms to address these problems will be presented. The Tech-X Chompst project aims at marrying the best of adaptive mesh refinement with linear matrix solver algorithms. The Tech-X code PolySwift++ is an SCFT simulation platform that leverages ongoing development in coupling Chombo, a package for solving PDEs via block-structured AMR calculations and embedded boundaries, with PETSc, a toolkit that includes a large assortment of sparse linear solvers.

A novel algorithm for delineating wetland depressions and ...

EPA Pesticide Factsheets

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features that are seldom fully filled with water. For instance, wetland depressions in the Prairie Pothole Region (PPR) are seasonally to permanently flooded wetlands characterized by nested hierarchical structures with dynamic filling- spilling-merging surface-water hydrological processes. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution LiDAR data and aerial imagery. We proposed a novel algorithm delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost path algorithm. The resulting flow network delineated putative temporary or seasonal flow paths connecting wetland depressions to each other or to the river network at scales finer than available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow modeling and hydrologic connectivity analysis. Presentation at AWRA Spring Specialty Conference in Sn

Restoring Wood-Rich Hotspots in Mountain Stream Networks

NASA Astrophysics Data System (ADS)

Wohl, E.; Scott, D.

2016-12-01

Mountain streams commonly include substantial longitudinal variability in valley and channel geometry, alternating repeatedly between steep, narrow and relatively wide, low gradient segments. Segments that are wider and lower gradient than neighboring steeper sections are hotspots with respect to: retention of large wood (LW) and finer sediment and organic matter; uptake of nutrients; and biomass and biodiversity of aquatic and riparian organisms. These segments are also more likely to be transport-limited with respect to floodplain and instream LW. Management designed to protect and restore riverine LW and the physical and ecological processes facilitated by the presence of LW is likely to be most effective if focused on relatively low-gradient stream segments. These segments can be identified using a simple, reach-scale gradient analysis based on high-resolution DEMs, with field visits to identify factors that potentially limit or facilitate LW recruitment and retention, such as forest disturbance history or land use. Drawing on field data from the western US, this presentation outlines a procedure for mapping relatively low-gradient segments in a stream network and for identifying those segments where LW reintroduction or retention is most likely to balance maximizing environmental benefits derived from the presence of LW while minimizing hazards associated with LW.

Effect of flour particle size on microstructural, rheological and physico-sensory characteristics of bread and south Indian parotta.

PubMed

Sakhare, Suresh D; Inamdar, Aashitosh A; Soumya, C; Indrani, D; Rao, G Venkateswara

2014-12-01

Wheat flour fractioned by sieving into four different particle size fractions namely finer fractions (<75 and 75-118 μm), coarser fractions (118-150 and >150 μm) were analyzed for their chemical, rheological, bread & parotta making characteristics. The finer fractions had lower ash, higher dry gluten, damaged starch and sodium dodecysulphate (SDS)-sedimentation value than the coarser fractions. The flour from finer fractions gave bread with best sensory and textural attributes. The parottas from finer fractions showed significantly higher sensory scores for colour, texture, layers, mouthfeel and overall quality score than the coarser fractions. In the micrograph of finer flour fractions, higher number of loosened single starch granules than the aggregates of starch and protein matrix were seen as compared to coarser fractions. These studies indicate that the flour from the finer fractions produce higher quality bread, parotta owing to the presence of higher damaged starch content, quantity and quality of protein in these fractions than coarser fractions.

Integrating Phenological, Trait and Environmental Data For Continental Scale Analysis: A Community Approach

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Walls, R.; Guralnick, R. P.; Rosemartin, A.; Deck, J.; Powers, L. A.

2014-12-01

There is a wealth of biodiversity and environmental data that can provide the basis for addressing global scale questions of societal concern. However, our ability to discover, access and integrate these data for use in broader analyses is hampered by the lack of standardized languages and systems. New tools (e.g. ontologies, data standards, integration tools, unique identifiers) are being developed that enable establishment of a framework for linked and open data. Relative to other domains, these tools are nascent in biodiversity and environmental sciences and will require effort to develop, though work can capitalize on lessons learned from previous efforts. Here we discuss needed next steps to provide consistently described and formatted ecological data for immediate application in ecological analysis, focusing on integrating phenology, trait and environmental data to understand local to continental-scale biophysical processes and inform natural resource management practices. As more sources of data become available at finer spatial and temporal resolution, e.g., from national standardized earth observing systems (e.g., NEON, LTER and LTAR Networks, USA NPN), these challenges will become more acute. Here we provide an overview of the standards and ontology development landscape specifically related to phenological and trait data, and identify requirements to overcome current challenges. Second, we outline a workflow for formatting and integrating existing datasets to address key scientific and resource management questions such as: "What traits determine differential phenological responses to changing environmental conditions?" or "What is the role of granularity of observation, and of spatiotemporal scale, in controlling phenological responses to different driving variables?" Third, we discuss methods to semantically annotate datasets to greatly decrease time needed to assemble heterogeneous data for use in ecological analyses on varying spatial scales. We close by making a call to interested community members for a working group to model phenology, trait and environmental data products from continental-scale efforts (e.g. NEON, USA-NPN and others) focusing on ways to assure discoverability and interoperability.

NASA Team Begins Testing of a New-Fangled Optic

NASA Image and Video Library

2017-12-08

It’s an age-old astronomical truth: To resolve smaller and smaller physical details of distant celestial objects, scientists need larger and larger light-collecting mirrors. This challenge is not easily overcome given the high cost and impracticality of building and — in the case of space observatories — launching large-aperture telescopes. However, a team of scientists and engineers at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, has begun testing a potentially more affordable alternative called the photon sieve. This new-fangled telescope optic could give scientists the resolution they need to see finer details still invisible with current observing tools – a jump in resolution that could help answer a 50-year-old question about the physical processes heating the sun's million-degree corona. Read more: go.nasa.gov/2abhanr Credit: NASA/Goddard/W. Hrybyk

Separation and Classification of Lipids Using Differential Ion Mobility Spectrometry

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

Shvartsburg, Alexandre A.; Isaac, Georgis; Leveque, Nathalie

2011-04-12

Correlations between the dimensions of a 2-D separation create trend lines that normally depend on structural or functional characteristics of the compound class and thus facilitate classification of unknowns. This broadly applies to conventional ion mobility spectrometry (IMS)/mass spectrometry (MS), where the major biomolecular classes (e.g., lipids, peptides, nucleotides) occupy different trend line domains. However, strong correlation between the IMS and MS separations for ions of same charge has impeded finer distinctions. Differential IMS (or FAIMS) is generally much less correlated to MS and thus should better separate the trend lines and associated domains. We report the first observation ofmore » chemical class separation by trend lines using FAIMS, here for lipids. For all lipids, FAIMS is indeed more independent of MS than conventional IMS, and subclasses (such as phospho-, glycero-, or sphingolipids) form distinct, often non-overlapping domains. Even finer categories with different functional groups or degrees of unsaturation are often separated. As expected, resolution improves in He-rich gases: at ~70% He, glycerolipid isomers with different positions of fatty acid attachment can be resolved. These results open the door for lipidomics application of FAIMS, particularly shotgun lipidomics and targeted analyses of bioactive lipids.« less

Utilization of satellite data for inventorying prairie ponds and lakes

NASA Technical Reports Server (NTRS)

Work, E. A., Jr.; Gilmer, D. S.

1976-01-01

ERTS-1 data were used in mapping open surface water features in the glaciated prairies. Emphasis was placed on the recognition of these features based upon water's uniquely low radiance in a single near-infrared waveband. On the basis of these results, thematic maps and statistics relating to open surface water were obtained. In a related effort, the added information content of multiple spectral wavebands was used for discriminating surface water at a level of detail finer than the virtual resolution of the data. The basic theory of this technique and some preliminary results are described.

Semiclassical propagator of the Wigner function.

PubMed

Dittrich, Thomas; Viviescas, Carlos; Sandoval, Luis

2006-02-24

Propagation of the Wigner function is studied on two levels of semiclassical propagation: one based on the Van Vleck propagator, the other on phase-space path integration. Leading quantum corrections to the classical Liouville propagator take the form of a time-dependent quantum spot. Its oscillatory structure depends on whether the underlying classical flow is elliptic or hyperbolic. It can be interpreted as the result of interference of a pair of classical trajectories, indicating how quantum coherences are to be propagated semiclassically in phase space. The phase-space path-integral approach allows for a finer resolution of the quantum spot in terms of Airy functions.

193nm high power lasers for the wide bandgap material processing

NASA Astrophysics Data System (ADS)

Fujimoto, Junichi; Kobayashi, Masakazu; Kakizaki, Koji; Oizumi, Hiroaki; Mimura, Toshio; Matsunaga, Takashi; Mizoguchi, Hakaru

2017-02-01

Recently infrared laser has faced resolution limit of finer micromachining requirement on especially semiconductor packaging like Fan-Out Wafer Level Package (FO-WLP) and Through Glass Via hole (TGV) which are hard to process with less defect. In this study, we investigated ablation rate with deep ultra violet excimer laser to explore its possibilities of micromachining on organic and glass interposers. These results were observed with a laser microscopy and Scanning Electron Microscope (SEM). As the ablation rates of both materials were quite affordable value, excimer laser is expected to be put in practical use for mass production.

Impacts of model spatial resolution on the vertical structure of convection in the tropics

NASA Astrophysics Data System (ADS)

Bui, Hien Xuan; Yu, Jia-Yuh; Chou, Chia

2018-02-01

This study examined the impacts of model horizontal resolution on vertical structures of convection in the tropics by performing sensitivity experiments with the NCAR CESM1. It was found that contributions to the total precipitation between top-heavy and bottom-heavy convection are different among various resolutions. A coarser resolution tends to produce a greater contribution from top-heavy convection and, as a result, stronger precipitation in the western Pacific ITCZ; while there is less contribution from bottom-heavy convection and weaker precipitation in the eastern Pacific ITCZ. In the western Pacific ITCZ, where the convection is dominated by a top-heavy structure, the stronger precipitation in coarser resolution experiments is due to changes in temperature and moisture profiles associated with a warmer environment (i.e., thermodynamical effect). In the eastern Pacific ITCZ, where the convection is dictated by a bottom-heavy structure, the stronger precipitation in finer resolution experiments comes from changes in convection structure (i.e., dynamic effect) which favors a greater contribution of bottom-heavy convection as the model resolution goes higher. The moisture budget analysis further suggested that the very different behavior in precipitation tendencies in response to model resolution changes between the western and eastern Pacific ITCZs are determined mainly by changes in convective structure rather than changes in convective strength. This study pointed out the importance of model spatial resolution in reproducing a reasonable contribution to the total precipitation between top-heavy and bottom-heavy structure of convection in the tropical Pacific ITCZs.

Cross-polar transport and scavenging of Siberian aerosols containing black carbon during the 2012 ACCESS summer campaign

NASA Astrophysics Data System (ADS)

Raut, Jean-Christophe; Marelle, Louis; Fast, Jerome D.; Thomas, Jennie L.; Weinzierl, Bernadett; Law, Katharine S.; Berg, Larry K.; Roiger, Anke; Easter, Richard C.; Heimerl, Katharina; Onishi, Tatsuo; Delanoë, Julien; Schlager, Hans

2017-09-01

During the ACCESS airborne campaign in July 2012, extensive boreal forest fires resulted in significant aerosol transport to the Arctic. A 10-day episode combining intense biomass burning over Siberia and low-pressure systems over the Arctic Ocean resulted in efficient transport of plumes containing black carbon (BC) towards the Arctic, mostly in the upper troposphere (6-8 km). A combination of in situ observations (DLR Falcon aircraft), satellite analysis and WRF-Chem simulations is used to understand the vertical and horizontal transport mechanisms of BC with a focus on the role of wet removal. Between the northwestern Norwegian coast and the Svalbard archipelago, the Falcon aircraft sampled plumes with enhanced CO concentrations up to 200 ppbv and BC mixing ratios up to 25 ng kg-1. During transport to the Arctic region, a large fraction of BC particles are scavenged by two wet deposition processes, namely wet removal by large-scale precipitation and removal in wet convective updrafts, with both processes contributing almost equally to the total accumulated deposition of BC. Our results underline that applying a finer horizontal resolution (40 instead of 100 km) improves the model performance, as it significantly reduces the overestimation of BC levels observed at a coarser resolution in the mid-troposphere. According to the simulations at 40 km, the transport efficiency of BC (TEBC) in biomass burning plumes was larger (60 %), because it was impacted by small accumulated precipitation along trajectory (1 mm). In contrast TEBC was small (< 30 %) and accumulated precipitation amounts were larger (5-10 mm) in plumes influenced by urban anthropogenic sources and flaring activities in northern Russia, resulting in transport to lower altitudes. TEBC due to large-scale precipitation is responsible for a sharp meridional gradient in the distribution of BC concentrations. Wet removal in cumulus clouds is the cause of modeled vertical gradient of TEBC, especially in the mid-latitudes, reflecting the distribution of convective precipitation, but is dominated in the Arctic region by the large-scale wet removal associated with the formation of stratocumulus clouds in the planetary boundary layer (PBL) that produce frequent drizzle.

Carbon-Nanotube-Based Electrodes for Biomedical Applications

NASA Technical Reports Server (NTRS)

Li, Jun; Meyyappan, M.

2008-01-01

A nanotube array based on vertically aligned nanotubes or carbon nanofibers has been invented for use in localized electrical stimulation and recording of electrical responses in selected regions of an animal body, especially including the brain. There are numerous established, emerging, and potential applications for localized electrical stimulation and/or recording, including treatment of Parkinson s disease, Tourette s syndrome, and chronic pain, and research on electrochemical effects involved in neurotransmission. Carbon-nanotube-based electrodes offer potential advantages over metal macroelectrodes (having diameters of the order of a millimeter) and microelectrodes (having various diameters ranging down to tens of microns) heretofore used in such applications. These advantages include the following: a) Stimuli and responses could be localized at finer scales of spatial and temporal resolution, which is at subcellular level, with fewer disturbances to, and less interference from, adjacent regions. b) There would be less risk of hemorrhage on implantation because nano-electrode-based probe tips could be configured to be less traumatic. c) Being more biocompatible than are metal electrodes, carbon-nanotube-based electrodes and arrays would be more suitable for long-term or permanent implantation. d) Unlike macro- and microelectrodes, a nano-electrode could penetrate a cell membrane with minimal disruption. Thus, for example, a nanoelectrode could be used to generate an action potential inside a neuron or in proximity of an active neuron zone. Such stimulation may be much more effective than is extra- or intracellular stimulation via a macro- or microelectrode. e) The large surface area of an array at a micron-scale footprint of non-insulated nanoelectrodes coated with a suitable electrochemically active material containing redox ingredients would make it possible to obtain a pseudocapacitance large enough to dissipate a relatively large amount of electric charge, so that a large stimulation current could be applied at a micron-scale region without exhausting the redox ingredients. f) Carbon nanotube array is more compatible with the three-dimensional network of tissues. Particularly, a better electrical-neural interface can be formed. g) A carbon nanotube array inlaid in insulating materials with only the ends exposed is an extremely sensitive electro-analysis tool that can measure the local neurotransmitter signal at extremely high sensitivity and temporal resolution.

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

Phillips, Claire L.; Bond-Lamberty, Ben; Desai, Ankur R.

A recent acceleration of model-data synthesis activities has leveraged many terrestrial carbon (C) datasets, but utilization of soil respiration (RS) data has not kept pace with other types such as eddy covariance (EC) fluxes and soil C stocks. Here we argue that RS data, including non-continuous measurements from survey sampling campaigns, have unrealized value and should be utilized more extensively and creatively in data synthesis and modeling activities. We identify three major challenges in interpreting RS data, and discuss opportunities to address them. The first challenge is that when RS is compared to ecosystem respiration (RECO) measured from EC towers,more » it is not uncommon to find substantial mismatch, indicating one or both flux methodologies are unreliable. We argue the most likely cause of mismatch is unreliable EC data, and there is an unrecognized opportunity to utilize RS for EC quality control. The second challenge is that RS integrates belowground heterotrophic (RH) and autotrophic (RA) activity, whereas modelers generally prefer partitioned fluxes, and few models include an explicit RS output. Opportunities exist to use the total RS flux for data assimilation and model benchmarking methods rather than less-certain partitioned fluxes. Pushing for more experiments that not only partition RS but also monitor the age of RA and RH, as well as for the development of belowground RA components in models, would allow for more direct comparison between measured and modeled values. The third challenge is that soil respiration is generally measured at a very different resolution than that needed for comparison to EC or ecosystem- to global-scale models. Measuring soil fluxes with finer spatial resolution and more extensive coverage, and downscaling EC fluxes to match the scale of RS, will improve chamber and tower comparisons. Opportunities also exist to estimate RH at regional scales by implementing decomposition functional types, akin to plant functional types. We conclude by discussing the benefits that wide use of RS data will bring to model development, and database developments that will make RS data more robust, useful, and broadly available to the research community.« less

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

El-Khoury, Patrick Z.; Ueltschi, Tyler W.; Mifflin, Amanda L.

Non-resonant tip-enhanced Raman images of 4,4'-dimercaptostilbene on silver reveal that different vibrational resonances of the reporter are selectively enhanced at different sites on the metal substrate. Sequentially recorded images track molecular diffusion within the diffraction-limited laser spot which illuminates the substrate. In effect, the recorded time resolved (Δt = 10 s) pixelated images (25 nm x 8 cm-1) broadcast molecule-local field interactions which take place on much finer scales.

Semantic classification of urban buildings combining VHR image and GIS data: An improved random forest approach

NASA Astrophysics Data System (ADS)

Du, Shihong; Zhang, Fangli; Zhang, Xiuyuan

2015-07-01

While most existing studies have focused on extracting geometric information on buildings, only a few have concentrated on semantic information. The lack of semantic information cannot satisfy many demands on resolving environmental and social issues. This study presents an approach to semantically classify buildings into much finer categories than those of existing studies by learning random forest (RF) classifier from a large number of imbalanced samples with high-dimensional features. First, a two-level segmentation mechanism combining GIS and VHR image produces single image objects at a large scale and intra-object components at a small scale. Second, a semi-supervised method chooses a large number of unbiased samples by considering the spatial proximity and intra-cluster similarity of buildings. Third, two important improvements in RF classifier are made: a voting-distribution ranked rule for reducing the influences of imbalanced samples on classification accuracy and a feature importance measurement for evaluating each feature's contribution to the recognition of each category. Fourth, the semantic classification of urban buildings is practically conducted in Beijing city, and the results demonstrate that the proposed approach is effective and accurate. The seven categories used in the study are finer than those in existing work and more helpful to studying many environmental and social problems.

Morphological evidence for discrete stocks of yellow perch in Lake Erie

USGS Publications Warehouse

Kocovsky, Patrick M.; Knight, Carey T.

2012-01-01

Identification and management of unique stocks of exploited fish species are high-priority management goals in the Laurentian Great Lakes. We analyzed whole-body morphometrics of 1430 yellow perch Perca flavescens captured during 2007–2009 from seven known spawning areas in Lake Erie to determine if morphometrics vary among sites and management units to assist in identification of spawning stocks of this heavily exploited species. Truss-based morphometrics (n = 21 measurements) were analyzed using principal component analysis followed by ANOVA of the first three principal components to determine whether yellow perch from the several sampling sites varied morphometrically. Duncan's multiple range test was used to determine which sites differed from one another to test whether morphometrics varied at scales finer than management unit. Morphometrics varied significantly among sites and annually, but differences among sites were much greater. Sites within the same management unit typically differed significantly from one another, indicating morphometric variation at a scale finer than management unit. These results are largely congruent with recently-published studies on genetic variation of yellow perch from many of the same sampling sites. Thus, our results provide additional evidence that there are discrete stocks of yellow perch in Lake Erie and that management units likely comprise multiple stocks.

Microscopic Image of Martian Surface Material on a Silicone Substrate

NASA Technical Reports Server (NTRS)

2008-01-01

[figure removed for brevity, see original site] Click on image for larger version of Figure 1

This image taken by the Optical Microscope on NASA's Phoenix Mars Lander shows soil sprinkled from the lander's Robot Arm scoop onto a silicone substrate. The substrate was then rotated in front of the microscope. This is the first sample collected and delivered for instrumental analysis onboard a planetary lander since NASA's Viking Mars missions of the 1970s. It is also the highest resolution image yet seen of Martian soil.

The image is dominated by fine particles close to the resolution of the microscope. These particles have formed clumps, which may be a smaller scale version of what has been observed by Phoenix during digging of the surface material.

The microscope took this image during Phoenix's Sol 17 (June 11), or the 17th Martian day after landing. The scale bar is 1 millimeter (0.04 inch).

Zooming in on the Martian Soil

In figure 1, three zoomed-in portions are shown with an image of Martian soil particles taken by the Optical Microscope on NASA's Phoenix Mars Lander.

The left zoom box shows a composite particle. The top of the particle has a green tinge, possibly indicating olivine. The bottom of the particle has been reimaged at a different focus position in black and white (middle zoom box), showing that this is a clump of finer particles.

The right zoom box shows a rounded, glassy particle, similar to those which have also been seen in an earlier sample of airfall dust collected on a surface exposed during landing.

The shadows at the bottom of image are of the beams of the Atomic Force Microscope.

The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

Statistical Modeling of Daily Stream Temperature for Mitigating Fish Mortality

NASA Astrophysics Data System (ADS)

Caldwell, R. J.; Rajagopalan, B.

2011-12-01

Water allocations in the Central Valley Project (CVP) of California require the consideration of short- and long-term needs of many socioeconomic factors including, but not limited to, agriculture, urban use, flood mitigation/control, and environmental concerns. The Endangered Species Act (ESA) ensures that the decision-making process provides sufficient water to limit the impact on protected species, such as salmon, in the Sacramento River Valley. Current decision support tools in the CVP were deemed inadequate by the National Marine Fisheries Service due to the limited temporal resolution of forecasts for monthly stream temperature and fish mortality. Finer scale temporal resolution is necessary to account for the stream temperature variations critical to salmon survival and reproduction. In addition, complementary, long-range tools are needed for monthly and seasonal management of water resources. We will present a Generalized Linear Model (GLM) framework of maximum daily stream temperatures and related attributes, such as: daily stream temperature range, exceedance/non-exceedance of critical threshold temperatures, and the number of hours of exceedance. A suite of predictors that impact stream temperatures are included in the models, including current and prior day values of streamflow, water temperatures of upstream releases from Shasta Dam, air temperature, and precipitation. Monthly models are developed for each stream temperature attribute at the Balls Ferry gauge, an EPA compliance point for meeting temperature criteria. The statistical framework is also coupled with seasonal climate forecasts using a stochastic weather generator to provide ensembles of stream temperature scenarios that can be used for seasonal scale water allocation planning and decisions. Short-term weather forecasts can also be used in the framework to provide near-term scenarios useful for making water release decisions on a daily basis. The framework can be easily translated to other locations and is intended to be a complement to the physical stream temperature modeling efforts that are underway on the river.

Spatial and temporal dynamics of commercial reef-fish fisheries on the West Florida Shelf: Understanding drivers of fleet behavior and the implications for future management

NASA Astrophysics Data System (ADS)

Cockrell, M.; Murawski, S. A.; Sanchirico, J. N.; O'Farrell, S.; Strelcheck, A.

2016-02-01

Spatial and temporal patterns of fishing activity have historically been described over relatively coarse scales or with limited datasets. However, new and innovative approaches for fisheries management will require an understanding of both species population dynamics and fleet behavior at finer spatial and temporal resolution. In this study we describe the spatial and temporal patterns of commercial reef-fish fisheries on the West Florida Shelf (WFS) from 2006-14, using a combination of on-board observer, catch logbook, and vessel satellite tracking data. The satellite tracking data is both high resolution (ie, records from each vessel at least once every hour for the duration of a trip), and required of all federally-permitted reef fish vessels in the Gulf of Mexico, making this a uniquely rich and powerful dataset. Along with spatial and temporal fishery dynamics, we quantified concomitant patterns in fishery economics and catch metrics, such as total landings and catch composition. Fishery patterns were correlated to a number of variables across the vessel, trip, and whole fleet scales, including vessel size, distance from home port, number of days at sea, and days available to fish. Notably, changes in management structure during the years examined (eg, establishment of a seasonal closed area in 2009 and implementation of an individual fishing quota system for Grouper-Tilefish in 2010), as well as emergency spatial closures during the Deepwater Horizon oil spill in 2010, enabled us to examine the impacts of specific management frameworks on the WFS reef-fish fishery. This research highlights the need to better understand the biological, economic, and social impacts within fisheries when managing for conservation and fisheries sustainability. We discuss our results in the context of a changing policy and management landscape for marine and coastal resources in the Gulf of Mexico.

Estimation of Trees Outside Forests using IRS High Resolution data by Object Based Image Analysis

NASA Astrophysics Data System (ADS)

Pujar, G. S.; Reddy, P. M.; Reddy, C. S.; Jha, C. S.; Dadhwal, V. K.

2014-11-01

Assessment of Trees outside forests (TOF) is widely being recognized as a pivotal theme, in sustainable natural resource management, due to their role in offering variety of goods, such as timber, fruits and fodder as well as services like water, carbon, biodiversity. Forest Conservation efforts involving reduction of deforestation and degradation may have to increasingly rely on alternatives provided by TOF in catering to economic demands in forest edges. Spatial information systems involving imaging, analysis and monitoring to achieve objectives under protocols like REDD+, require incorporation of information content from areas under forest as well as trees outside forests, to aid holistic decisions. In this perspective, automation in retrieving information on area under trees, growing outside forests, using high resolution imaging is essential so that measuring and verification of extant carbon pools, are strengthened. Retrieval of this tree cover is demonstrated herewith, using object based image analysis in a forest edge of dry deciduous forests of Eastern Ghats, in Khammam district of Telangana state of India. IRS high resolution panchromatic 2.5 m data (Cartosat-1 Orthorectified) used in tandem with 5.8 m multispectral LISS IV data, discerns tree crowns and clusters at a detailed scale and hence semi-automated approach is attempted to classify TOF from a pair of image from relatively crop and cloud free season. Object based image analysis(OBIA) approach as implemented in commercial suite of e-Cognition (Ver 8.9) consists of segmentation at user defined scale followed by application of wide range of spectral, textural and object geometry based parameters for classification. Software offers innovative blend of raster and vector features that can be juxtaposed flexibly, across scales horizontally or vertically. Segmentation was carried out at multiple scales to discern first the major land covers, such as forest, water, agriculture followed by that at a finer scale, within cultivated landscape. Latter scale aimed to segregate TOF in configurations such as individual or scattered crowns, linear formations and patch TOF. As per the adopted norms in India for defining tree cover, units up to 1 ha area were considered as candidate TOF. Classification of fine scale (at 10) segments was accomplished using size, shape and texture. A customised parameter involving ratio of area of segment to its main skeleton length discerned linear formations consistently. Texture of Cartosat-1 2.5 m data was also used segregate tree cover from smoother crop patches in patch TOF category. In view of the specificity of the landscape character, continuum of cultivated area (b) and pockets of cultivation within forest (c) as well as the entire study area (a) were considered as three envelopes for evaluating the accuracy of the method. Accuracies not less than 75.1 per cent were reported in all the envelopes with a kappa accuracy of not less than 0.58. Overall accuracy of entire study area was 75.9 per cent with Kappa of 0.59 followed by 75.1 per cent ( Kappa: 0.58 ) of agricultural landscape (b). In pockets of cultivation context(c) accuracy was higher at 79.2 per cent ( Kappa: 0.64 ) possibly due to smaller population. Assessment showed that 1,791 ha of 24,140 ha studied (7.42 %) was under tree cover as per the definitions adopted. Strength of accuracy demonstrated obviously points to the potential of IRS high resolution data combination in setting up procedures to monitor the TOF in Indian context using OBIA approach so as to cater to the evolving demands of resource assessment and monitoring.

Channel representation in physically based models coupling groundwater and surface water: pitfalls and how to avoid them.

PubMed

Käser, Daniel; Graf, Tobias; Cochand, Fabien; McLaren, Rob; Therrien, René; Brunner, Philip

2014-01-01

Recent models that couple three-dimensional subsurface flow with two-dimensional overland flow are valuable tools for quantifying complex groundwater/stream interactions and for evaluating their influence on watershed processes. For the modeler who is used to defining streams as a boundary condition, the representation of channels in integrated models raises a number of conceptual and technical issues. These models are far more sensitive to channel topography than conventional groundwater models. On all spatial scales, both the topography of a channel and its connection with the floodplain are important. For example, the geometry of river banks influences bank storage and overbank flooding; the slope of the river is a primary control on the behavior of a catchment; and at the finer scale bedform characteristics affect hyporheic exchange. Accurate data on streambed topography, however, are seldom available, and the spatial resolution of digital elevation models is typically too coarse in river environments, resulting in unrealistic or undulating streambeds. Modelers therefore perform some kind of manual yet often cumbersome correction to the available topography. In this context, the paper identifies some common pitfalls, and provides guidance to overcome these. Both aspects of topographic representation and mesh discretization are addressed. Additionally, two tutorials are provided to illustrate: (1) the interpolation of channel cross-sectional data and (2) the refinement of a mesh along a stream in areas of high topographic variability. © 2014, National Ground Water Association.

Saturn B Ring, Finer Than Ever

NASA Image and Video Library

2017-01-30

This image shows a region in Saturn's outer B ring. NASA's Cassini spacecraft viewed this area at a level of detail twice as high as it had ever been observed before. And from this view, it is clear that there are still finer details to uncover. Researchers have yet to determine what generated the rich structure seen in this view, but they hope detailed images like this will help them unravel the mystery. In order to preserve the finest details, this image has not been processed to remove the many small bright blemishes, which are created by cosmic rays and charged particle radiation near the planet. The image was taken in visible light with the Cassini spacecraft wide-angle camera on Dec. 18, 2016. The view was obtained at a distance of approximately 32,000 miles (51,000 kilometers) from the rings, and looks toward the unilluminated side of the rings. Image scale is about a quarter-mile (360 meters) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA21058

Nanotechnology in Dental Sciences: Moving towards a Finer Way of Doing Dentistry

PubMed Central

Uskoković, Vuk; Bertassoni, Luiz Eduardo

2010-01-01

Nanotechnologies are predicted to revolutionize: (a) the control over materials properties at ultrafine scales; and (b) the sensitivity of tools and devices applied in various scientific and technological fields. In this short review, we argue that dentistry will be no exception to this trend. Here, we present a dynamic view of dental tissues, an adoption of which may lead to finer, more effective and minimally invasive reparation approaches. By doing so, we aim at providing insights into some of the breakthroughs relevant to understanding the genesis of dental tissues at the nanostructural level or generating dental materials with nanoscale critical boundaries. The lineage of the progress of dental science, including the projected path along the presumed nanotechnological direction of research and clinical application is mentioned too. We conclude by claiming that dentistry should follow the trend of probing matter at nanoscale that currently dominates both materials and biological sciences in order to improve on the research strategies and clinical techniques that have traditionally rested on mechanistic assumptions. PMID:27103959

Landsat-based Earth Observations and Crowd-sourced Data Provide Near Real-time Monitoring of Chimpanzee Habitat

NASA Astrophysics Data System (ADS)

Nackoney, J.; Pintea, L.; Jantz, S.; Hansen, M.

2015-12-01

The endangered chimpanzee (Pan troglodytes) is threatened by habitat loss from resource extraction and land conversion, as well as hunting, disease and the illegal pet trade. It has been estimated that more than 70% of chimpanzee's tropical forest habitats in Africa are now threatened by land use change. Recent developments in remote sensing and cloud computing enable the use of satellite observations to provide a synoptic view of chimpanzee habitats at finer spatial and temporal resolutions that are locally relevant and consistent across the entire species' range. We present a practical Decision Support System to be used by the Jane Goodall Institute and partners to annually monitor and forecast chimpanzee habitat health in Africa. The system integrates Earth observations from 30-meter resolution Landsat data with a species-specific habitat model and a model forecasting future land use change, enhanced by crowd-sourced field data collected by local communities and rangers using the Open Data Kit app and Android mobile smartphones and tablets. While coarser-scale and static chimpanzee habitat models have been previously developed, this project is the first to develop a dynamic monitoring system updated annually via Earth observations data that will systematically monitor threats and changes in habitat over time. Since the chimpanzee is an important keystone, flagship and umbrella species, an annual chimpanzee habitat health index would support conservation goals of other species within its large 2.5 million sq. km range and could be an important indicator of overall ecosystem health of tropical forests in Africa.

The Sensitivity of Numerical Simulations of Cloud-Topped Boundary Layers to Cross-Grid Flow

NASA Astrophysics Data System (ADS)

Wyant, Matthew C.; Bretherton, Christopher S.; Blossey, Peter N.

2018-02-01

In mesoscale and global atmospheric simulations with large horizontal domains, strong horizontal flow across the grid is often unavoidable, but its effects on cloud-topped boundary layers have received comparatively little study. Here the effects of cross-grid flow on large-eddy simulations of stratocumulus and trade-cumulus marine boundary layers are studied across a range of grid resolutions (horizontal × vertical) between 500 m × 20 m and 35 m × 5 m. Three cases are simulated: DYCOMS nocturnal stratocumulus, BOMEX trade cumulus, and a GCSS stratocumulus-to-trade cumulus case. Simulations are performed with a stationary grid (with 4-8 m s-1 horizontal winds blowing through the cyclic domain) and a moving grid (equivalent to subtracting off a fixed vertically uniform horizontal wind) approximately matching the mean boundary-layer wind speed. For stratocumulus clouds, cross-grid flow produces two primary effects on stratocumulus clouds: a filtering of fine-scale resolved turbulent eddies, which reduces stratocumulus cloud-top entrainment, and a vertical broadening of the stratocumulus-top inversion which enhances cloud-top entrainment. With a coarse (20 m) vertical grid, the former effect dominates and leads to strong increases in cloud cover and LWP, especially as horizontal resolution is coarsened. With a finer (5 m) vertical grid, the latter effect is stronger and leads to small reductions in cloud cover and LWP. For the BOMEX trade cumulus case, cross-grid flow tends to produce fewer and larger clouds with higher LWP, especially for coarser vertical grid spacing. The results presented are robust to choice of scalar advection scheme and Courant number.

Cloud Computing-based Platform for Drought Decision-Making using Remote Sensing and Modeling Products: Preliminary Results for Brazil

NASA Astrophysics Data System (ADS)

Vivoni, E.; Mascaro, G.; Shupe, J. W.; Hiatt, C.; Potter, C. S.; Miller, R. L.; Stanley, J.; Abraham, T.; Castilla-Rubio, J.

2012-12-01

Droughts and their hydrological consequences are a major threat to food security throughout the world. In arid and semiarid regions dependent on irrigated agriculture, prolonged droughts lead to significant and recurring economic and social losses. In this contribution, we present preliminary results on integrating a set of multi-resolution drought indices into a cloud computing-based visualization platform. We focused our initial efforts on Brazil due to a severe, on-going drought in a large agricultural area in the northeastern part of the country. The online platform includes drought products developed from: (1) a MODIS-based water stress index (WSI) based on inferences from normalized difference vegetation index and land surface temperature fields, (2) a volumetric water content (VWC) index obtained from application of the NASA CASA model, and (3) a set of AVHRR-based vegetation health indices obtained from NOAA/NESDIS. The drought indices are also presented in terms of anomalies with respect to a baseline period. Since our main objective is to engage stakeholders and decision-makers in Brazil, we incorporated other relevant geospatial data into the platform, including irrigation areas, dams and reservoirs, administrative units and annual climate information. We will also present a set of use cases developed to help stakeholders explore, query and provide feedback that allowed fine-tuning of the drought product delivery, presentation and analysis tools. Finally, we discuss potential next steps in development of the online platform, including applications at finer resolutions in specific basins and at a coarser global scale.

Downscaling Global Emissions and Its Implications Derived from Climate Model Experiments

PubMed Central

Abe, Manabu; Kinoshita, Tsuguki; Hasegawa, Tomoko; Kawase, Hiroaki; Kushida, Kazuhide; Masui, Toshihiko; Oka, Kazutaka; Shiogama, Hideo; Takahashi, Kiyoshi; Tatebe, Hiroaki; Yoshikawa, Minoru

2017-01-01

In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10–30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods. PMID:28076446

An Improved Snake Model for Refinement of Lidar-Derived Building Roof Contours Using Aerial Images

NASA Astrophysics Data System (ADS)

Chen, Qi; Wang, Shugen; Liu, Xiuguo

2016-06-01

Building roof contours are considered as very important geometric data, which have been widely applied in many fields, including but not limited to urban planning, land investigation, change detection and military reconnaissance. Currently, the demand on building contours at a finer scale (especially in urban areas) has been raised in a growing number of studies such as urban environment quality assessment, urban sprawl monitoring and urban air pollution modelling. LiDAR is known as an effective means of acquiring 3D roof points with high elevation accuracy. However, the precision of the building contour obtained from LiDAR data is restricted by its relatively low scanning resolution. With the use of the texture information from high-resolution imagery, the precision can be improved. In this study, an improved snake model is proposed to refine the initial building contours extracted from LiDAR. First, an improved snake model is constructed with the constraints of the deviation angle, image gradient, and area. Then, the nodes of the contour are moved in a certain range to find the best optimized result using greedy algorithm. Considering both precision and efficiency, the candidate shift positions of the contour nodes are constrained, and the searching strategy for the candidate nodes is explicitly designed. The experiments on three datasets indicate that the proposed method for building contour refinement is effective and feasible. The average quality index is improved from 91.66% to 93.34%. The statistics of the evaluation results for every single building demonstrated that 77.0% of the total number of contours is updated with higher quality index.

An operational methodology for riparian land cover fine scale regional mapping for the study of landscape influence on river ecological status

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.

The spatiotemporal association of non-prescription retail sales with cases during the 2009 influenza pandemic in Great Britain.

PubMed

Todd, Stacy; Diggle, Peter J; White, Peter J; Fearne, Andrew; Read, Jonathan M

2014-04-29

To assess whether retail sales of non-prescription products can be used for syndromic surveillance and whether it can detect influenza activity at different spatial scales. A secondary objective was to assess whether changes in purchasing behaviour were related to public health advice or levels of media or public interest. The UK. National and regional influenza case estimates and retail sales from a major British supermarket. Weekly, seasonally adjusted sales of over-the-counter symptom remedies and non-pharmaceutical products; recommended as part of the advice offered by public health agencies; were compared with weekly influenza case estimates. Comparisons were made at national and regional spatial resolutions. We also compared sales to national measures of contemporaneous media output and public interest (Internet search volume) related to the pandemic. At a national scale there was no significant correlation between retail sales of symptom remedies and cases for the whole pandemic period in 2009. At the regional scale, a minority of regions showed statistically significant positive correlations between cases and sales of adult 'cold and flu' remedies and cough remedies (3.2%, 5/156, 3.8%, 6/156), but a greater number of regions showed a significant positive correlation between cases and symptomatic remedies for children (35.6%, 55/156). Significant positive correlations between cases and sales of thermometers and antiviral hand gels/wash were seen at both spatial scales (Cor 0.477 (95% CI 0.171 to 0.699); 0.711 (95% CI 0.495 to 0.844)). We found no significant association between retail sales and media reporting or Internet search volume. This study provides evidence that the British public responded appropriately to health messaging about hygiene. Non-prescription retail sales at a national level are not useful for the detection of cases. However, at finer spatial scales, in particular age-groups, retail sales may help augment existing surveillance and merit further study.

The spatiotemporal association of non-prescription retail sales with cases during the 2009 influenza pandemic in Great Britain

PubMed Central

Todd, Stacy; Diggle, Peter J; White, Peter J; Fearne, Andrew; Read, Jonathan M

2014-01-01

Objective To assess whether retail sales of non-prescription products can be used for syndromic surveillance and whether it can detect influenza activity at different spatial scales. A secondary objective was to assess whether changes in purchasing behaviour were related to public health advice or levels of media or public interest. Setting The UK. Participants National and regional influenza case estimates and retail sales from a major British supermarket. Outcome measures Weekly, seasonally adjusted sales of over-the-counter symptom remedies and non-pharmaceutical products; recommended as part of the advice offered by public health agencies; were compared with weekly influenza case estimates. Comparisons were made at national and regional spatial resolutions. We also compared sales to national measures of contemporaneous media output and public interest (Internet search volume) related to the pandemic. Results At a national scale there was no significant correlation between retail sales of symptom remedies and cases for the whole pandemic period in 2009. At the regional scale, a minority of regions showed statistically significant positive correlations between cases and sales of adult ‘cold and flu’ remedies and cough remedies (3.2%, 5/156, 3.8%, 6/156), but a greater number of regions showed a significant positive correlation between cases and symptomatic remedies for children (35.6%, 55/156). Significant positive correlations between cases and sales of thermometers and antiviral hand gels/wash were seen at both spatial scales (Cor 0.477 (95% CI 0.171 to 0.699); 0.711 (95% CI 0.495 to 0.844)). We found no significant association between retail sales and media reporting or Internet search volume. Conclusions This study provides evidence that the British public responded appropriately to health messaging about hygiene. Non-prescription retail sales at a national level are not useful for the detection of cases. However, at finer spatial scales, in particular age-groups, retail sales may help augment existing surveillance and merit further study. PMID:24780494

Multiscale properties of weighted total variation flow with applications to denoising and registration.

PubMed

Athavale, Prashant; Xu, Robert; Radau, Perry; Nachman, Adrian; Wright, Graham A

2015-07-01

Images consist of structures of varying scales: large scale structures such as flat regions, and small scale structures such as noise, textures, and rapidly oscillatory patterns. In the hierarchical (BV, L(2)) image decomposition, Tadmor, et al. (2004) start with extracting coarse scale structures from a given image, and successively extract finer structures from the residuals in each step of the iterative decomposition. We propose to begin instead by extracting the finest structures from the given image and then proceed to extract increasingly coarser structures. In most images, noise could be considered as a fine scale structure. Thus, starting the image decomposition with finer scales, rather than large scales, leads to fast denoising. We note that our approach turns out to be equivalent to the nonstationary regularization in Scherzer and Weickert (2000). The continuous limit of this procedure leads to a time-scaled version of total variation flow. Motivated by specific clinical applications, we introduce an image depending weight in the regularization functional, and study the corresponding weighted TV flow. We show that the edge-preserving property of the multiscale representation of an input image obtained with the weighted TV flow can be enhanced and localized by appropriate choice of the weight. We use this in developing an efficient and edge-preserving denoising algorithm with control on speed and localization properties. We examine analytical properties of the weighted TV flow that give precise information about the denoising speed and the rate of change of energy of the images. An additional contribution of the paper is to use the images obtained at different scales for robust multiscale registration. We show that the inherently multiscale nature of the weighted TV flow improved performance for registration of noisy cardiac MRI images, compared to other methods such as bilateral or Gaussian filtering. A clinical application of the multiscale registration algorithm is also demonstrated for aligning viability assessment magnetic resonance (MR) images from 8 patients with previous myocardial infarctions. Copyright © 2015. Published by Elsevier B.V.

Multiscale skeletal representation of images via Voronoi diagrams

NASA Astrophysics Data System (ADS)

Marston, R. E.; Shih, Jian C.

1995-08-01

Polygonal approximations to skeletal or stroke-based representations of 2D objects may consume less storage and be sufficient to describe their shape for many applications. Multi- scale descriptions of object outlines are well established but corresponding methods for skeletal descriptions have been slower to develop. In this paper we offer a method of generating scale-based skeletal representation via the Voronoi diagram. The method has the advantages of less time complexity, a closer relationship between the skeletons at each scale and better control over simplification of the skeleton at lower scales. This is because the algorithm starts by generating the skeleton at the coarsest scale first, then it produces each finer scale, in an iterative manner, directly from the level below. The skeletal approximations produced by the algorithm also benefit from a strong relationship with the object outline, due to the structure of the Voronoi diagram.

Accuracy Assessment of Satellite Derived Forest Cover Products in South and Southeast Asia

NASA Astrophysics Data System (ADS)

Gilani, H.; Xu, X.; Jain, A. K.

2017-12-01

South and Southeast Asia (SSEA) region occupies 16 % of worlds land area. It is home to over 50% of the world's population. The SSEA's countries are experiencing significant land-use and land-cover changes (LULCCs), primarily in agriculture, forest, and urban land. For this study, we compiled four existing global forest cover maps for year 2010 by Gong et al.(2015), Hansen et al. (2013), Sexton et al.(2013) and Shimada et al. (2014), which were all medium resolution (≤30 m) products based on Landsat and/or PALSAR satellite images. To evaluate the accuracy of these forest products, we used three types of information: (1) ground measurements, (2) high resolution satellite images and (3) forest cover maps produced at the national scale. The stratified random sampling technique was used to select a set of validation data points from the ground and high-resolution satellite images. Then the confusion matrix method was used to assess and rank the accuracy of the forest cover products for the entire SSEA region. We analyzed the spatial consistency of different forest cover maps, and further evaluated the consistency with terrain characteristics. Our study suggests that global forest cover mapping algorithms are trained and tested using limited ground measurement data. We found significant uncertainties in mountainous areas due to the topographical shadow effect and the dense tree canopies effects. The findings of this study will facilitate to improve our understanding of the forest cover dynamics and their impacts on the quantities and pathways of terrestrial carbon and nitrogen fluxes. Gong, P., et al. (2012). "Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data." International Journal of Remote Sensing 34(7): 2607-2654. Hansen, M. C., et al. (2013). "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science 342(6160): 850-853. Sexton, J. O., et al. (2013). "Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error." International Journal of Digital Earth: 1-22. Shimada, M., et al. (2014). "New global forest/non-forest maps from ALOS PALSAR data (2007-2010)." Remote Sensing of Environment 155: 13-31.

Geochemical heterogeneity of a gasoline-contaminated aquifer

USGS Publications Warehouse

Cozzarelli, Isabelle M.; Herman, Janet S.; Baedecker, Mary Jo; Fischer, Jeffrey M.

1999-01-01

The scale of biogeochemical reactions was studied in a physically and chemically heterogeneous surficial Coastal Plain aquifer contaminated by a gasoline spill. The physical heterogeneity of the aquifer is manifested in two hydrologic units, a shallow local aquifer of perched water and a regional sandy aquifer. Over the studied vertical interval of 21.3 ft (6.5 m), concentrations of reactive species varied by orders of magnitude, and the impact of biodegradation was expressed to widely varying degrees. A thin (3 ft thick) section of the perched-water zone was the most contaminated; total aromatic hydrocarbons were as high as 19.4 mg/l. Hydrocarbons were degraded by microbially mediated reactions that varied over short vertical distances and time. Anaerobic processes dominated within the low-permeability clay unit, whereas in the more permeable sandy layers nitrate reduction and aerobic degradation occurred. Hydrocarbons were more persistent over time in the low-permeability layer due to the limited availability of electron acceptors for degradation. The microbial degradation of hydrocarbons was linked to sulfate and iron reduction in the clay unit and led to alterations in the aquifer solids; electron microscopy revealed the presence of FeS minerals encrusting primary aquifer grains. High concentrations of Fe2+ in groundwater, up to 34.5 mg/l, persist in kinetic disequilibrium in the presence of elevated H2S levels of 1.0 mg/l. Assessment of aquifer heterogeneities and groundwater contamination was possible due to sample discrimination at a scale of approximately 2 ft (∼0.6 m), a much finer resolution than is attempted in many remedial investigations of polluted aquifers. The information obtained in this type of study is essential to the development of models capable of estimating the fate of hydrocarbons at a site scale.

Accounting for groundwater in stream fish thermal habitat responses to climate change

USGS Publications Warehouse

Snyder, Craig D.; Hitt, Nathaniel P.; Young, John A.

2015-01-01

Forecasting climate change effects on aquatic fauna and their habitat requires an understanding of how water temperature responds to changing air temperature (i.e., thermal sensitivity). Previous efforts to forecast climate effects on brook trout habitat have generally assumed uniform air-water temperature relationships over large areas that cannot account for groundwater inputs and other processes that operate at finer spatial scales. We developed regression models that accounted for groundwater influences on thermal sensitivity from measured air-water temperature relationships within forested watersheds in eastern North America (Shenandoah National Park, USA, 78 sites in 9 watersheds). We used these reach-scale models to forecast climate change effects on stream temperature and brook trout thermal habitat, and compared our results to previous forecasts based upon large-scale models. Observed stream temperatures were generally less sensitive to air temperature than previously assumed, and we attribute this to the moderating effect of shallow groundwater inputs. Predicted groundwater temperatures from air-water regression models corresponded well to observed groundwater temperatures elsewhere in the study area. Predictions of brook trout future habitat loss derived from our fine-grained models were far less pessimistic than those from prior models developed at coarser spatial resolutions. However, our models also revealed spatial variation in thermal sensitivity within and among catchments resulting in a patchy distribution of thermally suitable habitat. Habitat fragmentation due to thermal barriers therefore may have an increasingly important role for trout population viability in headwater streams. Our results demonstrate that simple adjustments to air-water temperature regression models can provide a powerful and cost-effective approach for predicting future stream temperatures while accounting for effects of groundwater.

Assessment of the effects of horizontal grid resolution on long ...

EPA Pesticide Factsheets

The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment.

Collaborative classification of hyperspectral and visible images with convolutional neural network

NASA Astrophysics Data System (ADS)

Zhang, Mengmeng; Li, Wei; Du, Qian

2017-10-01

Recent advances in remote sensing technology have made multisensor data available for the same area, and it is well-known that remote sensing data processing and analysis often benefit from multisource data fusion. Specifically, low spatial resolution of hyperspectral imagery (HSI) degrades the quality of the subsequent classification task while using visible (VIS) images with high spatial resolution enables high-fidelity spatial analysis. A collaborative classification framework is proposed to fuse HSI and VIS images for finer classification. First, the convolutional neural network model is employed to extract deep spectral features for HSI classification. Second, effective binarized statistical image features are learned as contextual basis vectors for the high-resolution VIS image, followed by a classifier. The proposed approach employs diversified data in a decision fusion, leading to an integration of the rich spectral information, spatial information, and statistical representation information. In particular, the proposed approach eliminates the potential problems of the curse of dimensionality and excessive computation time. The experiments evaluated on two standard data sets demonstrate better classification performance offered by this framework.

NASCAP simulation of PIX 2 experiments

NASA Technical Reports Server (NTRS)

Roche, J. C.; Mandell, M. J.

1985-01-01

The latest version of the NASCAP/LEO digital computer code used to simulate the PIX 2 experiment is discussed. NASCAP is a finite-element code and previous versions were restricted to a single fixed mesh size. As a consequence the resolution was dictated by the largest physical dimension to be modeled. The latest version of NASCAP/LEO can subdivide selected regions. This permitted the modeling of the overall Delta launch vehicle in the primary computational grid at a coarse resolution, with subdivided regions at finer resolution being used to pick up the details of the experiment module configuration. Langmuir probe data from the flight were used to estimate the space plasma density and temperature and the Delta ground potential relative to the space plasma. This information is needed for input to NASCAP. Because of the uncertainty or variability in the values of these parameters, it was necessary to explore a range around the nominal value in order to determine the variation in current collection. The flight data from PIX 2 were also compared with the results of the NASCAP simulation.

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe - Part 1: Model description and evaluation of meteorological predictions

NASA Astrophysics Data System (ADS)

Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.

2013-02-01

Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e. the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID) are conducted over western Europe. Part 1 describes the background information for the model comparison and simulation design, as well as the application of WRF for January and July 2001 over triple-nested domains in western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°. Six simulated meteorological variables (i.e. temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients of major meteorological variables. While the domainwide performance of T2, Q2, RH2, and WD10 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in WS10 and Precip even at 0.025°. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g. lack of soil temperature and moisture nudging), limitations in the physical parameterizations of the planetary boundary layer (e.g. cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g. snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvement for WS10, Precip, and some mesoscale events (e.g. strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. These results indicate a need to further improve the model representations of the above parameterizations at all scales.

Persistence characterization and data calibration scheme for the RSS-NIR H2RG detector on SALT

NASA Astrophysics Data System (ADS)

Mosby, Gregory; Eggen, Nathan; Wolf, Marsha; Jaehnig, Kurt; Kotulla, Ralf

2016-07-01

The University of Wisconsin Madison is building a NIR spectrograph (RSS-NIR) for the Southern African Large Telescope. The detector system uses a H2RG HdCdTe 1.7 μm cutoff array. We performed tests to measure and characterize the persistence of the detector to inform strategies to mitigate this effect. These tests use up-the- ramp group samples to get finer time resolution of the release of persistence. We share these test results. We also present preliminary results of the dependence of persistence on detector temperature. We conclude with an outline and assessment of a persistence calibration scheme.

Prostate Cancer Stem Cells: Viewing Signaling Cascades at a Finer Resolution.

PubMed

Lin, Xiukun; Farooqi, Ammad Ahmad; Qureshi, Muhammad Zahid; Romero, Mirna Azalea; Tabassum, Sobia; Ismail, Muhammad

2016-06-01

It is becoming characteristically more understandable that within tumor cells, there lies a sub-population of tumor cells with "stem cell" like properties and remarkable ability of self-renewal. Many features of these self-renewing cells are comparable with normal stem cells and are termed as "cancer stem cells". Accumulating experimentally verified data has started to scratch the surface of spatio-temporally dysregulated intracellular signaling cascades in the biology of prostate cancer stem cells. We partition this multicomponent review into how different signaling cascades operate in cancer stem cells and how bioactive ingredients isolated from natural sources may modulate signaling network.

Light Detection and Ranging (LIDAR) From Space - Laser Altimeters

NASA Technical Reports Server (NTRS)

Sun, Xiaoli

2016-01-01

Light detection and ranging, or lidar, is like radar but atoptical wavelengths. The principle of operation and theirapplications in remote sensing are similar. Lidars havemany advantages over radars in instrument designs andapplications because of the much shorter laser wavelengthsand narrower beams. The lidar transmitters and receiveroptics are much smaller than radar antenna dishes. Thespatial resolution of lidar measurement is much finer thanthat of radar because of the much smaller footprint size onground. Lidar measurements usually give a better temporalresolution because the laser pulses can be much narrowerthan radio frequency (RF) signals. The major limitation oflidar is the ability to penetrate clouds and ground surfaces.

Paleo-environmental Setting of the Murray Formation of Aeolis Mons, Gale Crater, Mars, as Explored by the Curiosity Rover

NASA Astrophysics Data System (ADS)

Lewis, K. W.; Fedo, C.; Grotzinger, J. P.; Gupta, S.; Stein, N.; Rivera-Hernandez, F.; Watkins, J. A.; Banham, S.; Edgett, K. S.; Minitti, M. E.; Schieber, J.; Edgar, L. A.; Siebach, K. L.; Stack, K.; Newsom, H. E.; House, C. H.; Sumner, D. Y.; Vasavada, A. R.

2017-12-01

Since landing, the Mars Science Laboratory Curiosity rover climbed 300 meters in elevation from the floor of north Gale crater up the lower northwest flank of Aeolis Mons ("Mount Sharp"). Nearly 200 meters of this ascent was accomplished in the 1.5 years alone, as the rover was driven up-section through the sedimentary rocks of the informally designated "Murray" formation. This unit comprises a large fraction of the lower strata of Mt. Sharp along the rover traverse. Our exploration of the Murray formation reveals a diverse suite of fine-grained facies. Grain sizes range from finer grains than can be resolved by the MAHLI imager (particles <62.5 microns) up to medium sand; the finer fraction comprises the bulk of the stratigraphy. Layering occurs at a range of scales; the majority is expressed as parallel laminae of mm-scale. Some sandy stratigraphic intervals exhibit cross-stratification at ripple (cm) and dune (m and larger) scales; the inferred bedforms are consistent with a range of subaqueous and aeolian depositional settings. Diagenetic features include locally variable occurrences of concretions and near-ubiquitous Ca-sulfate veins; these attest to extended interaction of the sediment with aqueous fluids in the subsurface. As a whole, the sedimentary facies of the Murray formation have been interpreted to record a predominately lacustrine paleo-environment, with likely subaerial aeolian and fluvial intervals. Further exploration, including the campaign at the hematite-bearing Vera Rubin Ridge, continues to reveal the complex and long-lived depositional history of the Gale crater basin.

The 2017 México Tsunami Record, Numerical Modeling and Threat Assessment in Costa Rica

NASA Astrophysics Data System (ADS)

Chacón-Barrantes, Silvia

2018-03-01

An M w 8.2 earthquake and tsunami occurred offshore the Pacific coast of México on 2017-09-08, at 04:49 UTC. Costa Rican tide gauges have registered a total of 21 local, regional and far-field tsunamis. The Quepos gauge registered 12 tsunamis between 1960 and 2014 before it was relocated inside a harbor by late 2014, where it registered two more tsunamis. This paper analyzes the 2017 México tsunami as recorded by the Quepos gauge. It took 2 h for the tsunami to arrive to Quepos, with a first peak height of 9.35 cm and a maximum amplitude of 18.8 cm occurring about 6 h later. As a decision support tool, this tsunami was modeled for Quepos in real time using ComMIT (Community Model Interface for Tsunami) with the finer grid having a resolution of 1 arcsec ( 30 m). However, the model did not replicate the tsunami record well, probably due to the lack of a finer and more accurate bathymetry. In 2014, the National Tsunami Monitoring System of Costa Rica (SINAMOT) was created, acting as a national tsunami warning center. The occurrence of the 2017 México tsunami raised concerns about warning dissemination mechanisms for most coastal communities in Costa Rica, due to its short travel time.

Oligotyping reveals differences between gut microbiomes of free-ranging sympatric Namibian carnivores (Acinonyx jubatus, Canis mesomelas) on a bacterial species-like level

PubMed Central

Menke, Sebastian; Wasimuddin; Meier, Matthias; Melzheimer, Jörg; Mfune, John K. E.; Heinrich, Sonja; Thalwitzer, Susanne; Wachter, Bettina; Sommer, Simone

2014-01-01

Recent gut microbiome studies in model organisms emphasize the effects of intrinsic and extrinsic factors on the variation of the bacterial composition and its impact on the overall health status of the host. Species occurring in the same habitat might share a similar microbiome, especially if they overlap in ecological and behavioral traits. So far, the natural variation in microbiomes of free-ranging wildlife species has not been thoroughly investigated. The few existing studies exploring microbiomes through 16S rRNA gene reads clustered sequencing reads into operational taxonomic units (OTUs) based on a similarity threshold (e.g., 97%). This approach, in combination with the low resolution of target databases, generally limits the level of taxonomic assignments to the genus level. However, distinguishing natural variation of microbiomes in healthy individuals from “abnormal” microbial compositions that affect host health requires knowledge of the “normal” microbial flora at a high taxonomic resolution. This gap can now be addressed using the recently published oligotyping approach, which can resolve closely related organisms into distinct oligotypes by utilizing subtle nucleotide variation. Here, we used Illumina MiSeq to sequence amplicons generated from the V4 region of the 16S rRNA gene to investigate the gut microbiome of two free-ranging sympatric Namibian carnivore species, the cheetah (Acinonyx jubatus) and the black-backed jackal (Canis mesomelas). Bacterial phyla with proportions >0.2% were identical for both species and included Firmicutes, Fusobacteria, Bacteroidetes, Proteobacteria and Actinobacteria. At a finer taxonomic resolution, black-backed jackals exhibited 69 bacterial taxa with proportions ≥0.1%, whereas cheetahs had only 42. Finally, oligotyping revealed that shared bacterial taxa consisted of distinct oligotype profiles. Thus, in contrast to 3% OTUs, oligotyping can detect fine-scale taxonomic differences between microbiomes. PMID:25352837

Evaluation of sliding baseline methods for spatial estimation for cluster detection in the biosurveillance system

PubMed Central

Xing, Jian; Burkom, Howard; Moniz, Linda; Edgerton, James; Leuze, Michael; Tokars, Jerome

2009-01-01

Background The Centers for Disease Control and Prevention's (CDC's) BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of the daily disease monitoring task. Our study focused on finding useful anomalies at manageable alert rates according to available BioSense data history. Methods The study dataset included more than 3 years of daily counts of military outpatient clinic visits for respiratory and rash syndrome groupings. We applied four spatial estimation methods in implementations of space-time scan statistics cross-checked in Matlab and C. We compared the utility of these methods according to the resultant background cluster rate (a false alarm surrogate) and sensitivity to injected cluster signals. The comparison runs used a spatial resolution based on the facility zip code in the patient record and a finer resolution based on the residence zip code. Results Simple estimation methods that account for day-of-week (DOW) data patterns yielded a clear advantage both in background cluster rate and in signal sensitivity. A 28-day baseline gave the most robust results for this estimation; the preferred baseline is long enough to remove daily fluctuations but short enough to reflect recent disease trends and data representation. Background cluster rates were lower for the rash syndrome counts than for the respiratory counts, likely because of seasonality and the large scale of the respiratory counts. Conclusion The spatial estimation method should be chosen according to characteristics of the selected data streams. In this dataset with strong day-of-week effects, the overall best detection performance was achieved using subregion averages over a 28-day baseline stratified by weekday or weekend/holiday behavior. Changing the estimation method for particular scenarios involving different spatial resolution or other syndromes can yield further improvement. PMID:19615075

Seasonal variability shapes resilience of small-scale fisheries in Baja California Sur, Mexico.

PubMed

Pellowe, Kara E; Leslie, Heather M

2017-01-01

Small-scale fisheries are an important source of food and livelihoods to coastal communities around the world. Understanding the seasonality of fisheries catch and composition is crucial to fisheries management, particularly in the context of changing environmental and socioeconomic conditions. While seasonal variability directly impacts the lives of fishers, most fisheries studies focus on longer-term change. Here we examine seasonal variability in the small-scale fisheries of Baja California Sur, Mexico based on 13 years of government fisheries data. We investigate how four fisheries indicators with direct relevance to ecological resilience-magnitude and variance of landed fish biomass, taxon richness and the proportion of top-trophic-level taxa in total catch-vary within and among years and at multiple spatial scales. We find that these resilience indicators vary both seasonally and spatially. These results highlight the value of finer-scale monitoring and management, particularly for data-poor fisheries.

Seasonal variability shapes resilience of small-scale fisheries in Baja California Sur, Mexico

PubMed Central

Leslie, Heather M.

2017-01-01

Small-scale fisheries are an important source of food and livelihoods to coastal communities around the world. Understanding the seasonality of fisheries catch and composition is crucial to fisheries management, particularly in the context of changing environmental and socioeconomic conditions. While seasonal variability directly impacts the lives of fishers, most fisheries studies focus on longer-term change. Here we examine seasonal variability in the small-scale fisheries of Baja California Sur, Mexico based on 13 years of government fisheries data. We investigate how four fisheries indicators with direct relevance to ecological resilience–magnitude and variance of landed fish biomass, taxon richness and the proportion of top-trophic-level taxa in total catch–vary within and among years and at multiple spatial scales. We find that these resilience indicators vary both seasonally and spatially. These results highlight the value of finer-scale monitoring and management, particularly for data-poor fisheries. PMID:28783740

Accelerated thermal and mechanical testing of CSP assemblies

NASA Technical Reports Server (NTRS)

Ghaffarian, R.

2000-01-01

Chip Scale Packages (CSP) are now widely used for many electronic applications including portable and telecommunication products. A test vehicle (TV-1) with eleven package types and pitches was built and tested by the JPL MicrotypeBGA Consortium during 1997 to 1999. Lessons learned by the team were published as a guidelines document for industry use. The finer pitch CSP packages which recently became available were indluded in the next test vehicle of the JPL CSP Consortium.

Frequency Resolved Nanoscale Chemical Imaging of 4,4'-Dimercaptostilbene on Silver

DOE PAGES

El-Khoury, Patrick Z.; Ueltschi, Tyler W.; Mifflin, Amanda L.; ...

2014-11-26

Non-resonant tip-enhanced Raman images of 4,4'-dimercaptostilbene on silver reveal that different vibrational resonances of the reporter are selectively enhanced at different sites on the metal substrate. Sequentially recorded images track molecular diffusion within the diffraction-limited laser spot which illuminates the substrate. In effect, the recorded time resolved (Δt = 10 s) pixelated images (25 nm x 8 cm-1) broadcast molecule-local field interactions which take place on much finer scales.

MO-FG-202-03: Efficient Data Collection of Continuous 2D and Discrete Relative Dosimetric Data for Annual LINAC QA Using TrueBeam Developer Mode and a 1D Scanning Tank

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

Knutson, N; Schmidt, M; University of Rhode Island, Kingston, RI

2016-06-15

Purpose: To develop a method to exploit real-time dynamic machine and couch parameter control during linear accelerator (LINAC) beam delivery to facilitate efficient performance of TG-142 suggested, Annual LINAC QA tests. Methods: Varian’s TrueBeam Developer Mode (Varian Medical Systems, Palo Alto, CA) facilitates control of Varian’s TrueBeam LINAC via instructions provided in Extensible Markup Language (XML) files. This allows machine and couch parameters to be varied dynamically, in real-time, during beam delivery. Custom XML files were created to allow for the collection of (1) continuous Tissue Maximum Ratios (TMRs), (2) beam profiles, and (3) continuous output factors using a 1D-scanningmore » tank. TMRs were acquired by orienting an ionization chamber (IC) at isocenter (depth=25cm) and synchronizing a depth scan towards the water surface while lowering the couch at 1mm/s. For beam profiles, the couch was driven laterally and longitudinally while logging IC electrometer readings. Output factors (OFs) where collected by continually varying field sizes (4×4 to 30×30-cm{sup 2}) at a constant speed of 6.66 mm/s. To validate measurements, comparisons were made to data collected using traditional methods (e.g. 1D or 3D tank). Results: All data collecting using the proposed methods agreed with traditionally collected data (TMRs within 1%, OFs within 0.5% and beam profile agreement within 1% / 1mm) while taking less time to collect (factor of approximately 1/10) and with a finer sample resolution. Conclusion: TrueBeam developer mode facilitates collection of continuous data with the same accuracy as traditionally collected data with a finer resolution in less time. Results demonstrate an order of magnitude increase in sampled resolution and an order of magnitude reduction in collection time compared to traditional acquisition methods (e.g. 3D scanning tank). We are currently extending this approach to perform other TG-142 tasks.« less

Initial Results in Global Flood Monitoring System (GFMS) Using GPM Data

NASA Astrophysics Data System (ADS)

Wu, H.; Adler, R. F.; Kirschbaum, D.; Huffman, G. J.; Tian, Y.

2016-12-01

The Global Flood Monitoring System (GFMS) (http://flood.umd.edu) has been developed and used to provide real-time flood detection and streamflow estimates over the last few years with significant success shown by validation against global flood event data sets and observed streamflow variations. It has become a tool for various national and international organizations to appraise flood conditions in various areas, including where rainfall and hydrology information is limited. The GFMS has been using the TRMM Multi-satellite Precipitation Analysis (TMPA) as its main rainfall input. Now, with the advent of NASA's Global Precipitation Measurement (GPM) mission there is an opportunity to significantly improve global flood monitoring and forecasting. GPM's Integrated Multi-satellitE Retrievals for GPM (IMERG) multi-satellite product is designed to take advantage of various technical advances in the field and combine that with an efficient processing system producing "early" (4 hrs) and "late" (12 hrs) products for operational use. The products are also more uniform in results than TMPA among the various satellites going into the analysis and available at finer time and space resolutions. On the road to replacing TMPA with the IMERG in the operational version of the GFMS parallel systems were run for periods to understand the impact of the new type of data on the streamflow and flood estimates. Results of this comparison are the basis for this presentation. It is expected that an improvement will be noted both in the accuracy of the precipitation estimates and a smoother transition in and out of heavy rain events, helping to reduce "shock" in the hydrology model. The finer spatial resolution should also help in this regard. The GFMS will be initially run at its primary resolution of 1/8th degree latitude/longitude with both data sets to isolate the impact of the rain information change. Other aspects will also be examined, including higher latitude events, where GPM precipitation algorithms should also provide improvements. This initial work will help focus full implementation of the IMERG into GFMS and the retrospective calculations to be done for the full TRMM/GPM era.

Fine-Scale Environmental Indicators of Public Health and Well ...

EPA Pesticide Factsheets

Urban ecosystem services contribute to public health and well-being by buffering natural and man-made hazards, and by promoting healthful lifestyles that include physical activity, social interaction, and engagement with nature. As part of the EnviroAtlas online mapping tool, EPA and its research partners have identified urban environmental features that have been linked in the scientific literature to specific aspects of public health and well-being. Examples of these features include tree cover along walkable roads, overall neighborhood green space, green window views, and proximity to parks. Associated aspects of health and well-being include physical fitness, social capital, school performance, and longevity. In many previous studies, stronger associations were observed in disproportionately vulnerable populations such as children, the elderly, and those of lower socioeconomic status.EnviroAtlas researchers have estimated and mapped a suite of urban environmental features by synthesizing newly-generated one-meter resolution landcover data, downscaled census population data, and existing datasets such as roads and waterways. Resulting geospatial metrics represent health-related indicators of urban ecosystem services supply and demand at the census block-group and finer. They have been developed using consistent methods to facilitate comparisons between neighborhoods and across multiple U.S. communities. Demographic overlays, also available in EnviroAtl

EnviroAtlas Connects Urban Ecosystem Services and Human ...

EPA Pesticide Factsheets

Ecosystem services in urban areas can improve public health and well-being by mitigating natural and anthropogenic pollution, and by promoting healthy lifestyles that include engagement with nature and enhanced opportunities for physical activity and social interaction. EPA’s EnviroAtlas online mapping tool identifies urban environmental features linked in the scientific and medical literature to specific aspects of public health and well-being. EnviroAtlas researchers have synthesized newly-generated one-meter resolution landcover data, downscaled census population data, and other existing datasets such as roads and parks. Resulting geospatial metrics represent health-related indicators of urban ecosystem services supply and demand by census block-group and finer scales. EnviroAtlas maps include percent of the population with limited window views of trees, tree cover along walkable roads, overall neighborhood green space, and proximity to parks. Demographic data can be overlaid to perform analyses of disproportionate distribution of urban ecosystem services across population groups. Together with the Eco-Health Relationship Browser, EnviroAtlas data can be linked to numerous aspects of public health and well-being including school performance, physical fitness, social capital, and longevity. EnviroAtlas maps have been developed using consistent methods to allow for comparisons between neighborhoods and across multiple U.S. communities. To feature eco-heal

Characterizing continuous urban growth using composited time-series Landsat data

NASA Astrophysics Data System (ADS)

Song, X. P.; Sexton, J. O.; Huang, C.; Feng, M.; Channan, S.; Baker, M. E.; Townshend, J. R.

2014-12-01

Impervious surfaces are land cover features through which water cannot penetrate into the soil. As an indicator of urban land use, impervious surface cover (ISC) is disproportionally important to human beings-although covering only 0.5% of the Earth's terrestrial surface, cities support over 50% the Earth's population. The increasing demand for built-up space by a growing urban population has been driving land use change in urban areas worldwide. An increase in ISC can significantly impact the biophysical characteristics of land surface, such as altering the local surface energy balance, or transforming regional hydrological systems. Remotely sensed data is commonly used as the primary data source for extracting impervious surface information for monitoring urban growth, but current studies often lack the sufficient temporal resolution or thematic detail to reveal the long-term, nonlinear development of impervious surfaces over time. In a previous study (Sexton et al. 2013), we created an annual stack of 30-m percent ISC estimates for the Washington DC-Baltimore metropolitan region from 1984 to 2010 by compositing all available Landsat images in the USGS archive. Here we developed a robust time-series method to detect impervious surface change. The method employs a customized logistic function for every pixel to model the continuous process of urban growth. It quantifies the fractional intensity of ISC change at the sub-pixel level and also characterizes the timing and length (in years) of urban development. The new method detects change based on a sequence of observations before, during and after change and thus is highly resistant to random noises. Our results showed that the DC-Baltimore metropolitan region experienced an accelerated growth pathway from the late 1980s to the late 2000s. The majority of urban and sub-urban development occurred at scales finer than the Landsat resolution (30 m), with a region-wide mean intensity of 46% ISC increase. Our study demonstrates the value of the long-term and fine temporal resolution data offered by the Landsat archive, and also highlights the possible limitations of Landsat's spatial resolution in characterizing continuous urban development.

REFLECT: Logiciel de restitution des reflectances au sol pour l'amelioration de la qualite de l'information extraite des images satellitales a haute resolution spatiale

NASA Astrophysics Data System (ADS)

Bouroubi, Mohamed Yacine

Multi-spectral satellite imagery, especially at high spatial resolution (finer than 30 m on the ground), represents an invaluable source of information for decision making in various domains in connection with natural resources management, environment preservation or urban planning and management. The mapping scales may range from local (finer resolution than 5 m) to regional (resolution coarser than 5m). The images are characterized by objects reflectance in the electromagnetic spectrum witch represents the key information in many applications. However, satellite sensor measurements are also affected by parasite input due to illumination and observation conditions, to the atmosphere, to topography and to sensor properties. Two questions have oriented this research. What is the best approach to retrieve surface reflectance with the measured values while taking into account these parasite factors? Is this retrieval a sine qua non condition for reliable image information extraction for the diverse domains of application for the images (mapping, environmental monitoring, landscape change detection, resources inventory, etc.)? The goals we have delineated for this research are as follow: (1) Develop software to retrieve ground reflectance while taking into account the aspects mentioned earlier. This software had to be modular enough to allow improvement and adaptation to diverse remote sensing application problems; and (2) Apply this software in various context (urban, agricultural, forest) and analyse results to evaluate the accuracy gain of extracted information from remote sensing imagery transformed in ground reflectance images to demonstrate the necessity of operating in this way, whatever the type of application. During this research, we have developed a tool to retrieve ground reflectance (the new version of the REFLECT software). This software is based on the formulas (and routines) of the 6S code (Second Simulation of Satellite Signal in the Solar Spectrum) and on the dark targets method to estimated the aerosol optical thickness, representing the most difficult factor to correct. Substantial improvements have been made to the existing models. These improvements essentially concern the aerosols properties (integration of a more recent model, improvement of the dark targets selection to estimate the AOD), the adjacency effect, the adaptation to most used high resolution (Landsat TM and ETM+, all HR SPOT 1 to 5, EO-1 ALI and ASTER) and very high resolution (QuickBird et Ikonos) sensors and the correction of topographic effects with a model that separate direct and diffuse solar radiation components and the adaptation of this model to forest canopy. Validation has shown that ground reflectance estimation with REFLECT is performed with an accuracy of approximately +/-0.01 in reflectance units (for in the visible, near-infrared and middle-infrared spectral bands) even for a surface with varying topography. This software has allowed demonstrating, through apparent reflectance simulations, how much parasite factors influencing numerical values of the images may alter the ground reflectance (errors ranging from 10 to 50%). REFLECT has also been used to examine the usefulness of ground reflectance instead of raw data for various common remote sensing applications in domains such as classification, change detection, agriculture and forestry. In most applications (multi-temporal change monitoring, use of vegetation indices, biophysical parameters estimation, etc.) image correction is a crucial step to obtain reliable results. From the computer environment standpoint, REFLECT is organized as a series of menus, corresponding to different steps of: input parameters introducing, gas transmittances calculation, AOD estimation, and finally image correction application, with the possibility of using the fast option witch process an image of 5000 by 5000 pixels in approximately 15 minutes. (Abstract shortened by UMI.)

Characterizing the Siple Coast Ice Stream System using Satellite Images, Improved Topography, and Integrated Aerogeophysical Measurements

NASA Technical Reports Server (NTRS)

Scambos, Ted

2003-01-01

A technique for improving elevation maps of the polar ice sheets has been developed using AVHRR images. The technique is based on 'photoclinometry' or 'shape from shading', a technique used in the past for mapping planetary surfaces where little elevation information was available. The fundamental idea behind photoclinometry is using the brightness of imaged areas to infer their surface slope in the sun-illuminated direction. Our version of the method relies on a calibration of the images based on an existing lower-resolution digital elevation model (DEM), and then using the images to improve the input DEM resolution to the scale of the image data. Most current DEMs covering the ice sheets are based on Radar altimetry data, and have an inherent resolution of 10 to 25 km at best - although the grid scale of the DEM is often finer. These DEMs are highly accurate (to less than 1 meter); but they report the mean elevation of a broad area, thus erasing smaller features of glaciological interest. AVHRR image data, when accurately geolocated and calibrated, provides surface slope measurements (based on the pixel brightness under known lighting conditions) every approximately 1.1 km. The limitations of the technique are noisiness in the image data, small variations in the albedo of the snow surface, and the integration technique used to create an elevation field from the image-derived slopes. Our study applied the technique to several ice sheet areas having some elevation data; Greenland, the Amery Ice Shelf, the Institute Ice Stream, and the Siple Coast. For the latter, the input data set was laser-altimetry data collected under NSF's SOAR Facility (Support Office for Aerogeophysical Research) over the onset area of the Siple Coast. Over the course of the grant, the technique was greatly improved and modified, significantly improving accuracy and reducing noise from the images. Several publications resulted from the work, and a follow-on proposal to NASA has been submitted to apply the same method to MODIS data using ICESat and other elevation input information. This follow-on grant will explore two applications that are facilitated by the improved surface morphology characterizations of the ice sheets: accumulation and temperature variations near small undulations in the ice.

A high resolution global scale groundwater model

NASA Astrophysics Data System (ADS)

de Graaf, Inge; Sutanudjaja, Edwin; van Beek, Rens; Bierkens, Marc

2014-05-01

As the world's largest accessible source of freshwater, groundwater plays a vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and supplies water for agricultural and industrial activities. During times of drought, groundwater storage provides a large natural buffer against water shortage and sustains flows to rivers and wetlands, supporting ecosystem habitats and biodiversity. Yet, the current generation of global scale hydrological models (GHMs) do not include a groundwater flow component, although it is a crucial part of the hydrological cycle. Thus, a realistic physical representation of the groundwater system that allows for the simulation of groundwater head dynamics and lateral flows is essential for GHMs that increasingly run at finer resolution. In this study we present a global groundwater model with a resolution of 5 arc-minutes (approximately 10 km at the equator) using MODFLOW (McDonald and Harbaugh, 1988). With this global groundwater model we eventually intend to simulate the changes in the groundwater system over time that result from variations in recharge and abstraction. Aquifer schematization and properties of this groundwater model were developed from available global lithological maps and datasets (Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moosdorf, 2013), combined with our estimate of aquifer thickness for sedimentary basins. We forced the groundwater model with the output from the global hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the net groundwater recharge and average surface water levels derived from routed channel discharge. For the parameterization, we relied entirely on available global datasets and did not calibrate the model so that it can equally be expanded to data poor environments. Based on our sensitivity analysis, in which we run the model with various hydrogeological parameter settings, we observed that most variance in groundwater depth is explained by variation in saturated conductivity, and, for the sediment basins, also by variation in recharge. We validated simulated groundwater heads with piezometer heads (available from www.glowasis.eu), resulting in a coefficient of determination for sedimentary basins of 0.92 with regression constant of 0.8. This shows the used method is suitable to build a global groundwater model using best available global information, and estimated water table depths are within acceptable accuracy in many parts of the world.

Performance of European chemistry transport models as function of horizontal resolution

NASA Astrophysics Data System (ADS)

Schaap, M.; Cuvelier, C.; Hendriks, C.; Bessagnet, B.; Baldasano, J. M.; Colette, A.; Thunis, P.; Karam, D.; Fagerli, H.; Graff, A.; Kranenburg, R.; Nyiri, A.; Pay, M. T.; Rouïl, L.; Schulz, M.; Simpson, D.; Stern, R.; Terrenoire, E.; Wind, P.

2015-07-01

Air pollution causes adverse effects on human health as well as ecosystems and crop yield and also has an impact on climate change trough short-lived climate forcers. To design mitigation strategies for air pollution, 3D Chemistry Transport Models (CTMs) have been developed to support the decision process. Increases in model resolution may provide more accurate and detailed information, but will cubically increase computational costs and pose additional challenges concerning high resolution input data. The motivation for the present study was therefore to explore the impact of using finer horizontal grid resolution for policy support applications of the European Monitoring and Evaluation Programme (EMEP) model within the Long Range Transboundary Air Pollution (LRTAP) convention. The goal was to determine the "optimum resolution" at which additional computational efforts do not provide increased model performance using presently available input data. Five regional CTMs performed four runs for 2009 over Europe at different horizontal resolutions. The models' responses to an increase in resolution are broadly consistent for all models. The largest response was found for NO2 followed by PM10 and O3. Model resolution does not impact model performance for rural background conditions. However, increasing model resolution improves the model performance at stations in and near large conglomerations. The statistical evaluation showed that the increased resolution better reproduces the spatial gradients in pollution regimes, but does not help to improve significantly the model performance for reproducing observed temporal variability. This study clearly shows that increasing model resolution is advantageous, and that leaving a resolution of 50 km in favour of a resolution between 10 and 20 km is practical and worthwhile. As about 70% of the model response to grid resolution is determined by the difference in the spatial emission distribution, improved emission allocation procedures at high spatial and temporal resolution are a crucial factor for further model resolution improvements.

Are satellite products good proxies for gauge precipitation over Singapore?

NASA Astrophysics Data System (ADS)

Hur, Jina; Raghavan, Srivatsan V.; Nguyen, Ngoc Son; Liong, Shie-Yui

2018-05-01

The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000-2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate model simulated future projections, when information on precipitation extremes need to be reliable as they are highly crucial for adaptation and mitigation.

Fine-scale assessment of home ranges and activity patterns for resident black vultures (Coragyps atratus) and turkey vultures (Cathartes aura)

DOE PAGES

Holland, Amanda E.; Byrne, Michael E.; Bryan, A. Lawrence; ...

2017-07-05

Knowledge of black vulture (Coragyps atratus) and turkey vulture (Cathartes aura) spatial ecology is surprisingly limited despite their vital ecological roles. Fine-scale assessments of space use patterns and resource selection are particularly lacking, although development of tracking technologies has allowed data collection at finer temporal and spatial resolution. The objectives of this study were to conduct the first assessment of monthly home range and core area sizes of resident black and turkey vultures with consideration to sex, as well as elucidate differences in monthly, seasonal, and annual activity patterns based on fine-scale movement data analyses. We collected 2.8-million locations formore » 9 black and 9 turkey vultures from June 2013 –August 2015 using solar-powered GSM/GPS transmitters. We quantified home ranges and core areas using the dynamic Brownian bridge movement model and evaluated differences as a function of species, sex, and month. Mean monthly home ranges for turkey vultures were ~50% larger than those of black vultures, although mean core area sizes did not differ between species. Turkey vulture home ranges varied little across months, with exception to a notable reduction in space-use in May, which corresponds with timing of chick-rearing activities. Black vulture home ranges and core areas as well as turkey vulture core areas were larger in breeding season months (January–April). Comparison of space use between male and female vultures was only possible for black vultures, and space use was only slightly larger for females during breeding months (February–May). Analysis of activity patterns revealed turkey vultures spend more time in flight and switch motion states (between flight and stationary) more frequently than black vultures across temporal scales. Our study reveals substantive variability in space use and activity rates between sympatric black and turkey vultures, providing insights into potential behavioral mechanisms contributing to niche differentiation between these species.« less

Fine-scale assessment of home ranges and activity patterns for resident black vultures (Coragyps atratus) and turkey vultures (Cathartes aura)

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

Holland, Amanda E.; Byrne, Michael E.; Bryan, A. Lawrence

Knowledge of black vulture (Coragyps atratus) and turkey vulture (Cathartes aura) spatial ecology is surprisingly limited despite their vital ecological roles. Fine-scale assessments of space use patterns and resource selection are particularly lacking, although development of tracking technologies has allowed data collection at finer temporal and spatial resolution. The objectives of this study were to conduct the first assessment of monthly home range and core area sizes of resident black and turkey vultures with consideration to sex, as well as elucidate differences in monthly, seasonal, and annual activity patterns based on fine-scale movement data analyses. We collected 2.8-million locations formore » 9 black and 9 turkey vultures from June 2013 –August 2015 using solar-powered GSM/GPS transmitters. We quantified home ranges and core areas using the dynamic Brownian bridge movement model and evaluated differences as a function of species, sex, and month. Mean monthly home ranges for turkey vultures were ~50% larger than those of black vultures, although mean core area sizes did not differ between species. Turkey vulture home ranges varied little across months, with exception to a notable reduction in space-use in May, which corresponds with timing of chick-rearing activities. Black vulture home ranges and core areas as well as turkey vulture core areas were larger in breeding season months (January–April). Comparison of space use between male and female vultures was only possible for black vultures, and space use was only slightly larger for females during breeding months (February–May). Analysis of activity patterns revealed turkey vultures spend more time in flight and switch motion states (between flight and stationary) more frequently than black vultures across temporal scales. Our study reveals substantive variability in space use and activity rates between sympatric black and turkey vultures, providing insights into potential behavioral mechanisms contributing to niche differentiation between these species.« less

Geology and geochronology of the Tana Basin, Ethiopia: LIP volcanism, super eruptions and Eocene-Oligocene environmental change

NASA Astrophysics Data System (ADS)

Prave, A. R.; Bates, C. R.; Donaldson, C. H.; Toland, H.; Condon, D. J.; Mark, D.; Raub, T. D.

2016-06-01

New geological and geochronological data define four episodes of volcanism for the Lake Tana region in the northern Ethiopian portion of the Afro-Arabian Large Igneous Province (LIP): pre-31 Ma flood basalt that yielded a single 40Ar/39Ar age of 34.05 ± 0.54 / 0.56 Ma; thick and extensive felsic ignimbrites and rhyolites (minimum volume of 2- 3 ×103 km3) erupted between 31.108 ± 0.020 / 0.041 Ma and 30.844 ± 0.027 / 0.046 Ma (U-Pb CA-ID-TIMS zircon ages); mafic volcanism bracketed by 40Ar/39Ar ages of 28.90 ± 0.12 / 0.14 Ma and 23.75 ± 0.02 / 0.04 Ma; and localised scoraceous basalt with an 40Ar/39Ar age of 0.033 ± 0.005 / 0.005 Ma. The felsic volcanism was the product of super eruptions that created a 60-80 km diameter caldera marked by km-scale caldera-collapse fault blocks and a steep-sided basin filled with a minimum of 180 m of sediment and the present-day Lake Tana. These new data enable mapping, with a finer resolution than previously possible, Afro-Arabian LIP volcanism onto the timeline of the Eocene-Oligocene transition and show that neither the mafic nor silicic volcanism coincides directly with perturbations in the geochemical records that span that transition. Our results reinforce the view that it is not the development of a LIP alone but its rate of effusion that contributes to inducing global-scale environmental change.

Genetic diversity and structure of Megabalanus azoricus in the Azores: Implications for aquaculture management

NASA Astrophysics Data System (ADS)

De Girolamo, Mirko; Torboli, Valentina; Pallavicini, Alberto; Isidro, Eduardo

2017-11-01

Megabalanus azoricus giant barnacles are the most traditional seafood of the Azores archipelago (NE Atlantic). This valuable commercial species has been highly exploited in the past and it is considered one of the key species for the development of aquaculture in the region. Despite the importance for conservation and aquaculture there is still a lack of basic information about M. azoricus genetic diversity and population structure. Here we used seven microsatellites markers to analyse 300 samples collected at six out of nine islands of the Azores archipelago, including also different locations from a single island, to provide information on the scale of genetic diversity and population structure of this species. Parameters like heterozygosity, allelic richness and effective number of alleles indicated a high genetic diversity and variability among islands. Pairwise comparisons and PCoA analysis on FST and Jost's DEST showed significant and evident differentiation among sampling locations. Additionally, AMOVA allocates a small (6.02%) but statistically significant portion of the variance to the among Island level revealing also a weak resolution (1.87%) at finer scale. Additionally Monte Carlo resampling methods indicated the most likely sources of the recruits were the local or adjacent populations. Genetic risks associated with the giant barnacle potential production scheme should be taken into account in a future management plan delimiting, as precautionary measure, this culture at a single island or at groups of islands here identified. Moreover a monitoring strategy should be implemented with the aim to evaluate possible changes in genetic parameters of native populations.

4D Imaging of Salt Precipitation during Evaporation from Saline Porous Media Influenced by the Particle Size Distribution

NASA Astrophysics Data System (ADS)

Norouzi Rad, M.; Shokri, N.

2014-12-01

Understanding the physics of water evaporation from saline porous media is important in many processes such as evaporation from porous media, vegetation, plant growth, biodiversity in soil, and durability of building materials. To investigate the effect of particle size distribution on the dynamics of salt precipitation in saline porous media during evaporation, we applied X-ray micro-tomography technique. Six samples of quartz sand with different grain size distributions were used in the present study enabling us to constrain the effects of particle and pore sizes on salt precipitation patterns and dynamics. The pore size distributions were computed using the pore-scale X-ray images. The packed beds were saturated with NaCl solution of 3 Molal and the X-ray imaging was continued for one day with temporal resolution of 30 min resulting in pore scale information about the evaporation and precipitation dynamics. Our results show more precipitation at the early stage of the evaporation in the case of sand with the larger particle size due to the presence of fewer evaporation sites at the surface. The presence of more preferential evaporation sites at the surface of finer sands significantly modified the patterns and thickness of the salt crust deposited on the surface such that a thinner salt crust was formed in the case of sand with smaller particle size covering larger area at the surface as opposed to the thicker patchy crusts in samples with larger particle sizes. Our results provide new insights regarding the physics of salt precipitation in porous media during evaporation.

Validation of satellite daily rainfall estimates in complex terrain of Bali Island, Indonesia

NASA Astrophysics Data System (ADS)

Rahmawati, Novi; Lubczynski, Maciek W.

2017-11-01

Satellite rainfall products have different performances in different geographic regions under different physical and climatological conditions. In this study, the objective was to select the most reliable and accurate satellite rainfall products for specific, environmental conditions of Bali Island. The performances of four spatio-temporal satellite rainfall products, i.e., CMORPH25, CMORPH8, TRMM, and PERSIANN, were evaluated at the island, zonation (applying elevation and climatology as constraints), and pixel scales, using (i) descriptive statistics and (ii) categorical statistics, including bias decomposition. The results showed that all the satellite products had low accuracy because of spatial scale effect, daily resolution and the island complexity. That accuracy was relatively lower in (i) dry seasons and dry climatic zones than in wet seasons and wet climatic zones; (ii) pixels jointly covered by sea and mountainous land than in pixels covered by land or by sea only; and (iii) topographically diverse than uniform terrains. CMORPH25, CMORPH8, and TRMM underestimated and PERSIANN overestimated rainfall when comparing them to gauged rain. The CMORPH25 had relatively the best performance and the PERSIANN had the worst performance in the Bali Island. The CMORPH25 had the lowest statistical errors, the lowest miss, and the highest hit rainfall events; it also had the lowest miss rainfall bias and was relatively the most accurate in detecting, frequent in Bali, ≤ 20 mm day-1 rain events. Lastly, the CMORPH25 coarse grid better represented rainfall events from coastal to inlands areas than other satellite products, including finer grid CMORPH8.

Using NextRAD sequencing to infer movement of herbivores among host plants.

PubMed

Fu, Zhen; Epstein, Brendan; Kelley, Joanna L; Zheng, Qi; Bergland, Alan O; Castillo Carrillo, Carmen I; Jensen, Andrew S; Dahan, Jennifer; Karasev, Alexander V; Snyder, William E

2017-01-01

Herbivores often move among spatially interspersed host plants, tracking high-quality resources through space and time. This dispersal is of particular interest for vectors of plant pathogens. Existing molecular tools to track such movement have yielded important insights, but often provide insufficient genetic resolution to infer spread at finer spatiotemporal scales. Here, we explore the use of Nextera-tagmented reductively-amplified DNA (NextRAD) sequencing to infer movement of a highly-mobile winged insect, the potato psyllid (Bactericera cockerelli), among host plants. The psyllid vectors the pathogen that causes zebra chip disease in potato (Solanum tuberosum), but understanding and managing the spread of this pathogen is limited by uncertainty about the insect's host plant(s) outside of the growing season. We identified 1,978 polymorphic loci among psyllids separated spatiotemporally on potato or in patches of bittersweet nightshade (S. dulcumara), a weedy plant proposed to be the source of potato-colonizing psyllids. A subset of the psyllids on potato exhibited genetic similarity to insects on nightshade, consistent with regular movement between these two host plants. However, a second subset of potato-collected psyllids was genetically distinct from those collected on bittersweet nightshade; this suggests that a currently unrecognized source, i.e., other nightshade patches or a third host-plant species, could be contributing to psyllid populations in potato. Oftentimes, dispersal of vectors of pathogens must be tracked at a fine scale in order to understand, predict, and manage disease spread. We demonstrate that emerging sequencing technologies that detect genome-wide SNPs of a vector can be used to infer such localized movement.

Comparison of satellite reflectance algorithms for estimating ...

EPA Pesticide Factsheets

We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop simple proxies for algal blooms and to facilitate portability between multispectral satellite imagers for regional algal bloom monitoring. Narrow band hyperspectral aircraft images were upscaled spectrally and spatially to simulate 5 current and near future satellite imaging systems. Established and new Chl-a algorithms were then applied to the synthetic satellite images and then compared to calibrated Chl-a water truth measurements collected from 44 sites within one hour of aircraft acquisition of the imagery. Masks based on the spatial resolution of the synthetic satellite imagery were then applied to eliminate mixed pixels including vegetated shorelines. Medium-resolution Landsat and finer resolution data were evaluated against 29 coincident water truth sites. Coarse-resolution MODIS and MERIS-like data were evaluated against 9 coincident water truth sites. Each synthetic satellite data set was then evaluated for the performance of a variety of spectrally appropriate algorithms with regard to the estimation of Chl-a concentrations against the water truth data set. The goal is to inform water resource decisions on the appropriate satellite data acquisition and processing for the es

High-Resolution Atmospheric Emission Inventory of the Argentine Enery Sector

NASA Astrophysics Data System (ADS)

Puliafito, Salvador Enrique; Castesana, Paula; Allende, David; Ruggeri, Florencia; Pinto, Sebastián; Pascual, Romina; Bolaño Ortiz, Tomás; Fernandez, Rafael Pedro

2017-04-01

This study presents a high-resolution spatially disaggregated inventory (2.5 km x 2.5 km), updated to 2014, of the main emissions from energy activities in Argentina. This inventory was created with the purpose of improving air quality regional models. The sub-sectors considered are public electricity and heat production, cement production, domestic aviation, road and rail transportation, inland navigation, residential and commercial, and fugitive emissions from refineries and fuel expenditure. The pollutants considered include greenhouse gases and ozone precursors: CO2, CH4, NOx, N2O VOC; and other gases specifically related to air quality including PM10, PM2.5, SOx, Pb and POPs. The uncertainty analysis of the inventories resulted in a variability of 3% for public electricity generation, 3-6% in the residential, commercial sector, 6-12% terrestrial transportation sector, 10-20% in oil refining and cement production according to the considered pollutant. Aviation and maritime navigation resulted in a higher variability reaching more than 60%. A comparison with the international emission inventory EDGAR shows disagreements in the spatial distribution of emissions, probably due to the finer resolution of the map presented here, particularly as a result of the use of new spatially disaggregated data of higher resolution that is currently available.