118 research outputs found
Erratum: All-sky search for gravitational-wave bursts in the first joint LIGO-GEO-Virgo run (Physical Review D - Particles, Fields, Gravitation and Cosmology (2010) 81 (102001))
No full textThis paper was published online on 5 May 2010 with an omission in the Collaboration author list. S. Dwyer has been
added as of 12 April 2012. The Collaboration author list is incorrect in the printed version of the journal
Erratum: Search for gravitational waves from compact binary coalescence in LIGO and Virgo data from S5 and VSR1 (Physical Review D - Particles, Fields, Gravitation and Cosmology)
No full textThis paper was published online on 5 November 2010 with an omission in the Collaboration author list. S. Dwyer has
been added as of 12 April 2012. The Collaboration author list is incorrect in the printed version of the journal
Publisher's Note: Search for gravitational waves from binary black hole inspiral, merger, and ringdown
No full textThis paper was published online on 6 June 2011 with an omission in the Collaboration author list. S. Dwyer has been
added as of 12 April 2012. The Collaboration author list is incorrect in the printed version of the journal
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Assessing the effectiveness of riparian restoration projects using Landsat and precipitation data from the cloud-computing application ClimateEngine.org
No full textRiparian vegetation along streams provides a suite of ecosystem services in rangelands and thus is the target of restoration when degraded by over-grazing, erosion, incision, or other disturbances. Assessments of restoration effectiveness depend on defensible monitoring data, which can be both expensive and difficult to collect. We present a method and case study to evaluate the effectiveness of restoration of riparian vegetation using a web-based cloud-computing and visualization tool (ClimateEngine.org) to access and process remote sensing and climate data. Restoration efforts on an Eastern Oregon ranch were assessed by analyzing the riparian areas of four creeks that had in-stream restoration structures constructed between 2008 and 2011. Within each study area, we retrieved spatially and temporally aggregated values of summer (June, July, August) normalized difference vegetation index (NDVI) and total precipitation for each water year (October-September) from 1984 to 2017. We established a pre-restoration (1984-2007) linear regression between total water year precipitation and summer NDVI for each study area, and then compared the post-restoration (2012-2017) data to this pre-restoration relationship. In each study area, the post-restoration NDVI-precipitation relationship was statistically distinct from the pre-restoration relationship, suggesting a change in the fundamental relationship between precipitation and NDVI resulting from stream restoration. We infer that the in-stream structures, which raised the water table in the adjacent riparian areas, provided additional water to the streamside vegetation that was not available before restoration and reduced the dependence of riparian vegetation on precipitation. This approach provides a cost-effective, quantitative method for assessing the effects of stream restoration projects on riparian vegetation
LIGO: the Laser Interferometer Gravitational-Wave Observatory
No full textThe goal of the Laser Interferometric Gravitational-Wave Observatory (LIGO) is to detect and study gravitational waves (GWs) of astrophysical origin. Direct detection of GWs holds the promise of testing general relativity in the strong-field regime, of providing a new probe of exotic objects such as black holes and neutron stars and of uncovering unanticipated new astrophysics. LIGO, a joint Caltech-MIT project supported by the National Science Foundation, operates three multi-kilometer interferometers at two widely separated sites in the United States. These detectors are the result of decades of worldwide technology development, design, construction and commissioning. They are now operating at their design sensitivity, and are sensitive to gravitational wave strains smaller than one part in 1021. With this unprecedented sensitivity, the data are being analyzed to detect or place limits on GWs from a variety of potential astrophysical sources
Search for gravitational waves associated with the August 2006 timing glitch of the Vela pulsar
No full textThe physical mechanisms responsible for pulsar timing glitches are thought to excite quasinormal mode oscillations in their parent neutron star that couple to gravitational-wave emission. In August 2006, a timing glitch was observed in the radio emission of PSR B0833-45, the Vela pulsar. At the time of the glitch, the two colocated Hanford gravitational-wave detectors of the Laser Interferometer Gravitational wave observatory (LIGO) were operational and taking data as part of the fifth LIGO science run (S5). We present the first direct search for the gravitational-wave emission associated with oscillations of the fundamental quadrupole mode excited by a pulsar timing glitch. No gravitational-wave detection
candidate was found. We place Bayesian 90% confidence upper limits of 6.3 x 10^(-21) to 1.4 x 10^(-20) on the peak intrinsic strain amplitude of gravitational-wave ring-down signals, depending on which spherical harmonic mode is excited. The corresponding range of energy upper limits is 5.0 x 10^(-44) to 1.3 x 10^(-45) erg
Search for gravitational waves from intermediate mass binary black holes
No full textWe present the results of a weakly modeled burst search for gravitational waves from mergers of nonspinning intermediate mass black holes in the total mass range 100–450 M⊙ and with the component mass ratios between 1∶1 and 4∶1. The search was conducted on data collected by the LIGO and Virgo detectors between November of 2005 and October of 2007. No plausible signals were observed by the search which constrains the astrophysical rates of the intermediate mass black holes mergers as a function of the component masses. In the most efficiently detected bin centered on 88+88 M⊙, for nonspinning sources, the rate density upper limit is 0.13 per Mpc3 per Myr at the 90% confidence level
Oregon hydrologic area agricultural field boundaries and field level and hydrologic unit water use data
No full text<p>The data was developed for the USGS Water-Use and Data Research program grant opportunities G20AS00053 and G21AS00258, combined with fundnig from Oregon Water Resources Department to improve estimates of water use from irrigated lands in Oregon. These data contain attributes of irrigation status, irrigation source type, crop type, irrigation method, assumed irrigation efficiency, irrigation water source, evapotranspiration (ET) data from OpenET, and effective precipitation developed using the USBR ET Demands model. Thee data were aggregated in order to further the development of estimates of applied water at the field-scale.</p><p>Funding provided by: United States Geological Survey<br>Crossref Funder Registry ID: https://ror.org/035a68863<br>Award Number: G21AS00258</p><p>Funding provided by: United States Geological Survey<br>Crossref Funder Registry ID: https://ror.org/035a68863<br>Award Number: G20AS00053</p><p>Funding provided by: Oregon Water Resources Department<br>Crossref Funder Registry ID: https://ror.org/02xbecd21<br>Award Number: </p><p>A single set of draft field boundaries for all agricultural lands were developed to represent the maximum extent of irrigated lands from 1985-2020 (digitized at the 1:5,000 scale). The approach used for this task was relatively straight forward yet time consuming and required careful attention to detail to avoid numerous potential pitfalls. Agricultural field boundaries were developed within a GIS system by modifying existing 2007 USDA Common Land Unit (CLU) data, OWRD drawn field boundaries (e.g., Malheur Lake Basin) and developing field boundaries from scratch where needed. This entailed: 1) using Common Land Unit (CLU) as-is where the quality and representativeness of the linework was deemed suitable; 2) modifying the CLU data to eliminate duplicates, overlaps, and slivers within the linework, and make representative of maximum agricultural extent; 3) manually digitizing new field boundaries where they do not currently exist; and 4) QAQC all results.</p>
<p>Crop type and irrigation status rasters and field-level summaries were derived from the USDA Cropland Data Layer (CDL) (USDA, 2019) and the open-source IrrMapper model (Ketchum et al., 2020). IrrMapper uses a Random Forest (RF) modeling approach to predict four land classes of irrigated agriculture, dryland agriculture, uncultivated lands, and wetlands at an annual time step, and at 30 m spatial resolution across the Western U.S. IrrMapper was used in this project to produce rasters of these classes for 2016-2022. For the attribution of agricultural field boundaries, the native IrrMapper values were aggregated into 2 classifications; a value of '1' representing irrigated conditions and '0' representing non-irrigated conditions. For each year, mapped field polygons were included in HUC-12 ET and irrigated acreage summaries if the irrigation status value was greater than 0.4 (40% of IrrMapper pixels in polygon are classified as irrigated). Crop type classification was based on the mode (i.e., majority) of CDL crop type pixels contained by the individual field geometry.</p>
<p>Irrigation system type was determined based on available data including OWRD place of use, water right, and water source information, high-resolution aerial images, and expert knowledge of agricultural practices in Oregon. The primary sources of imagery used for irrigation system type attribution was sourced from OSIP acquired in 2017 and 2018 at ~0.3m (1 ft pixel resolution) (State of Oregon: Oregon Geospatial Enterprise Office - Oregon Statewide Imagery Program, n.d.) and the 2020 series of aerial imagery from the National Agriculture Imagery Program (NAIP) (National Agriculture Imagery Program (NAIP), 2019) acquired at 60 cm (2 ft pixel resolution). Fields were attributed using the following irrigation system types: 0 - Developed/No longer irrigated; 1 - Sprinkler-Pivot-Linear; 2 - Sprinkler-Other (Wheel Line, Hand Line, Solid Set, Big Gun, Travelling Gun, Pods); 3 - Flood-Uncontrolled (Wild Flood) and No Apparent Irrigation Equipment; 4 - Flood-Controlled (Land Leveling, Borders, Basins, Furrows); 5 - Micro (Micro Sprinklers, Drip Lines, Subsurface Drip).</p>
<p>An irrigation efficiency value, assumed to represent the ratio of ET of applied water divided by the total applied water, was assigned to each agricultural field based on the system type attribute. Average values of irrigation efficiency for each system type category were based on values in the Washington Department of Ecology Report "Determining Irrigation Efficiency and Consumptive Use" (Washington State Department of Ecology, 2005).</p>
<p>Fields digitized by the DRI team were attributed by OWRD staff with one of the following irrigation source types: groundwater irrigated (GW), surface water irrigated (SW), or a combination of groundwater and surface water (GW&SW). The geometries represented in the shapefile are attributed using the following categories: 1 =GW irrigated, 2 = SW irrigated, and 3 = Combination.</p>
<p>Estimates of irrigation application rates were developed using spatially averaged field-scale OpenET ensemble ET estimates, effective precipitation developed from ET Demands, and irrigation efficiency attributes collected by OWRD. Application rates were estimated as: Application Rate = (ET – effective precipitation) / irrigation efficiency) </p>
<p>This approach resulted in many timesteps where effective precipitation was greater than ET, which resulted in negative Net ET. This negative Net ET was interpreted as a surplus of water contained within the represented unit of soil. As vegetation response lags irrigation activity, it is a certainty that irrigation or precipitation events occur during one calendar month, with a corresponding increase in ET and vegetation vigor observed in the following month. To account for this asynchronous relationship, negative Net ET was carried over to the following calendar month. This carry-over was repeated until positive Net ET values accounted for the surplus water condition. The applied water calculation was initialized using data developed prior to the 2016 water year, therefore all data associated with 2016 is considered valid.<br><br></p>
<p>Citations:</p>
<p>Beamer, J., & Hoskinson, M. (2021). <em>Historical Irrigation Water Use and Groundwater Pumpage Estimates in the Harney Basin, Oregon, 1991-2018</em>. State of Oregon Water Resources Department.</p>
<p>Bromley, M.; Minor, B. A.; Pearson, C.; Beamer, J.; Dunkerly, C. W.; Ott, T.; Huntington, J. L.; Hoskinson, M. (2023). <em>Evapotranspiration, Net Irrigation Water Requirements, and Reservoir Evaporation Estimates for Oregon</em>. Desert Research Institute – Draft report prepared for Oregon Water Resources Department.</p>
<p>Melton, F. S., Huntington, J. L., Grimm, R., Herring, J., Rollison, D., Erickson, T., Allen, R., Anderson, M., Fisher, J. B., Kilic, A., Senay, G. B., Volk, J., Hain, C., Johnson, L., Ruhoff, A., Blankenau, P., Bromley, M., Carrara, W., Daudert, B., Doherty, C., Dunkerly, C., Friedrichs, M., Guzman, A., Halverson, G., Hansen, J., Harding, J., Kang, Y., Ketchum, D., Minor, B., Morton, C., Ortega-Salazar, S., Ott, T., Ozdogan, M., ReVelle, P. M., Schull, M., Wang, C., Yang, Y., & Anderson, R. G. (2021). OpenET: Filling a critical data gap in water management for the western United States. <em>JAWRA Journal of the American Water Resources Association</em>, 58(6): 971-994. <a href="https://doi.org/10.1111/1752-1688.12956">https://doi.org/10.1111/1752-1688.12956</a></p>
<p>National Agriculture Imagery Program (NAIP). (2020). [Data set]. DOI/USGS/EROS. <a href="https://catalog.data.gov/dataset/national-agriculture-imagery-program-naip">https://catalog.data.gov/dataset/national-agriculture-imagery-program-naip</a></p>
<p>State of Oregon: Oregon Geospatial Enterprise Office - Oregon Statewide Imagery Program. (n.d.). https://www.oregon.gov/geo/Pages/imagery.aspx</p>
<p>USDA NRCS. (1993). Part 623 National Engineering Handbook, Chapter 2, Irrigation Water Requirements.</p>
<p>Washington State Department of Ecology, 2005, Determining Irrigation Efficiency and Consumptive Use: Washington State Department of Ecology GUID-1210.</p>
Search for gravitational-wave bursts in the first year of the fifth LIGO science run
No full textWe present the results obtained from an all-sky search for gravitational-wave (GW) bursts in the 64–2000 Hz frequency range in data collected by the LIGO detectors during the first year (November 2005—November 2006) of their fifth science run. The total analyzed live time was 268.6 days. Multiple hierarchical data analysis methods were invoked in this search. The overall sensitivity expressed in terms of the root-sum-square (rss) strain amplitude h[subscript rss] for gravitational-wave bursts with various morphologies was in the range of 6×10[superscript -22] Hz[superscript -1/2] to a few×10-[superscript 21] Hz[superscript -1/2]. No GW signals were observed and a frequentist upper limit of 3.75 events per year on the rate of strong GW bursts was placed at the 90% confidence level. As in our previous searches, we also combined this rate limit with the detection efficiency for selected waveform morphologies to obtain event rate versus strength exclusion curves. In sensitivity, these exclusion curves are the most stringent to date.Alfred P. Sloan FoundationResearch CorporationDavid and Lucile Packard FoundationLeverhulme TrustCarnegie TrustNational Aeronautics and Space AdministrationScottish Universities Physics AllianceScottish Funding CouncilRoyal Society, United KingdomConselleria d’Economia Hisenda i Innovació of the Govern de les Illes BalearsSpanish Ministerio de Educación y CienciaIstituto Nazionale di Fisica Nucleare of ItalyCouncil of Scientific and Industrial Research of IndiaAustralian Research CouncilState of Niedersachsen in GermanyMax-Planck-SocietyScience and Technology Facilities Council of the United KingdomNational Science Foundatio
Search for gravitational wave ringdowns from perturbed black holes in LIGO S4 data
No full textAccording to general relativity a perturbed black hole will settle to a stationary configuration by the emission of gravitational radiation. Such a perturbation will occur, for example, in the coalescence of a black hole binary, following their inspiral and subsequent merger. At late times the waveform is a superposition of quasinormal modes, which we refer to as the ringdown. The dominant mode is expected to be the fundamental mode, l=m=2. Since this is a well-known waveform, matched filtering can be implemented to search for this signal using LIGO data. We present a search for gravitational waves from black hole ringdowns in the fourth LIGO science run S4, during which LIGO was sensitive to the dominant mode of perturbed black holes with masses in the range of 10M[subscript ⊙] to 500M[subscript ⊙], the regime of intermediate-mass black holes, to distances up to 300 Mpc. We present a search for gravitational waves from black hole ringdowns using data from S4. No gravitational wave candidates were found; we place a 90%-confidence upper limit on the rate of ringdowns from black holes with mass between 85M[subscript ⊙] and 390M[subscript ⊙] in the local universe, assuming a uniform distribution of sources, of 3.2×10[superscript -5] yr[superscript -1] Mpc[superscript -3]=1.6×10[superscript -3] yr[superscript -1]L10[superscript -1],where L[subscript 10] is 10[superscript 10] times the solar blue-light luminosity.Alfred P. Sloan FoundationResearch CorporationDavid and Lucile Packard FoundationLeverhulme TrustCarnegie TrustNational Aeronautics and Space AdministrationScottish Universities Physics AllianceScottish Funding CouncilConselleria d’Economia, Hisenda i Innovació of the Govern de les Illes BalearsMinisterio de Ciencia e Innovación, SpainIstituto Nazionale di Fisica Nucleare of ItalyCouncil of Scientific and Industrial Research of IndiaAustralian Research CouncilState of Niedersachsen, GermanyMax Planck Society for the Advancement of ScienceScience and Technology Facilities Council, United KingdomNational Science Foundatio
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