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This is one of the CPC?s Monthly Atmospheric and SST Indices. It is the 850-hPa trade wind anomalies averaged over the area 5oN ? 5oS, 175oW-140oW (central equatorial Pacific). The anomalies are departures from the 1981-2010 base period means. Positive values indicate easterly anomalies.

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The success of the International Space Station in meeting NASA?s goals for completing the maximum amount of scientific research aboard the orbiting outpost is directly related to the proportion of astronaut time spent on scientific endeavors versus the time spent maintaining all of the ISS facility resources. In order to reduce the amount of crew time involved with inventory and logistics activities, the research and development of a highly automated, robust, scalable inventory and object tracking system based on recent advances in commercially available Surface Acoustic Wave passive ID tags is proposed. Through the combination of monitoring the movement of equipment and expendables through hatches, monitoring the contents of storage racks on a periodic basis, and by providing searching capabilities for particular objects, the system would significantly reduce crew workload, improve crew efficiency, and provide ground personnel with expanded knowledge of the on-board configuration of vehicle resources. The use of passive SAW tags will ultimately provide for lower cost tags with extended reading range, lower emissions, and expanded temperature range since the tag is not rectifying transmitted energy in order to power active circuits. In addition to the network of readers, PC software will be developed for simple crew interfacing.

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EDFacts Title III/Limited English Proficiency 2011-12 (EDFacts T3/LEP:2011-12) is one of 17 'topics' identified in the EDFacts documentation (in this database, each 'topic' is entered as a separate study); program data is available since 2005 at . EDFacts T3/LEP:2011-12 (ed.gov/about/inits/ed/edfacts) annually collects cross-sectional data from states to support oversight and reporting of programs for the education of limited English proficient students as contained in Title I and Title III of the Elementary and Secondary Education Act (ESEA), as amended. Title III also provides programs for students who are immigrants at the SEA and LEA levels. EDFacts T3/LEP:2011-12 data were collected using the EDFacts Submission System (ESS), a centralized portal and their submission by states is mandatory and required for benefits. Not submitting the required reports by a state constitutes a failure to comply with law and may have consequences for federal funding to the state. Key statistics produced from EDFacts T3/LEP:2011-12 are from 13 data groups: AMAO I LEP Making Progress, AMAO II LEP English Attainment, AMAO III AYP for LEP, Immigrant, LEP Enrolled, LEP Students in LEP Program, LEP English Language Proficiency Results, LEP English Language Proficiency Test, Title III Teachers, Title III LEP English Language Proficiency Results, Title III LEP English Language Proficiency Test, Title III LEP Students Served, and Title III Former LEP Students. For the purposes of this system, data groups are referred to as 'variables', as a result of the structure and format of EDFacts' data.

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This Atlas provides access to an array of public data on Federal farm programs that will allow users to visually explore a core component of U.S. agricultural policy. These programs assist farmers in sustaining and promoting the viability of their farm businesses or in protecting and enhancing the environment.

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The 2011 BRFSS data reflects a change in weighting methodology (raking) and the addition of cell phone only respondents. Shifts in observed prevalence from 2010 to 2011 for BRFSS measures will likely reflect the new methods of measuring risk factors, rather than true trends in risk-factor prevalence. A break in trend lines after 2010 is used to reflect this change in methodolgy. Percentages are weighted to population characteristics. Data are not available if it did not meet BRFSS stability requirements. For more information on these requirements, as well as risk factors and calculated variables, see the Technical Documents and Survey Data for a specific year - http://www.cdc.gov/brfss/annual_data/annual_data.htm. Recommended citation: Centers for Disease Control and Prevention (CDC). Behavioral Risk Factor Surveillance System. Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, [appropriate year].

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HUD's Real Estate Assessment Center conducts physical property inspections of properties that are owned, insured or subsidized by HUD, including public housing and multifamily assisted housing. About 20,000 such inspections are conducted each year to ensure that assisted families have housing that is decent, safe, sanitary and in good repair. This page provides a full historical view of the results of those inspections, providing point-in-time property scores. Results are available for download as a comma-delimited dataset. Separate datasets are available for public housing and for multifamily assisted properties. The results represent the inspections conducted from 2001 through January 2015. The dataset includes property identifiers and location information. Detailed descriptions of the inspection processes can be found in Federal Register notices 66 FR 59084 for public housing and 65 FR77230 for Office of Housing programs. Making these inspection details available will enable researchers, advocacy groups and the general public to 1) better understand the physical condition of the HUD-assisted housing stock, as well as changes in the stock over time; 2) hold providers accountable for housing quality; and 3) plan for future affordable housing needs.

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NOTICE: A significant issue with the precipitation variables in this dataset was found in January 2015. The precipitation data has two fewer columns than the temperature data, one from each edge. When merged into the same coordinate system, this caused the temperature data to be offset to the west by one pixel. The dataset is now broken into two sub-datasets, one for precipitation and one for temperature. This corrects the pixel location. Any use of precipitation data from this dataset from September 2013, when new precipitation files containing the issue were introduced, should be considered slightly in error. For more information please contact gdp@usgs.gov. In this project, we used an advanced statistical downscaling method that combines high-resolution observations with outputs from 16 different global climate models based on 4 future emission scenarios to generate the most comprehensive dataset of daily temperature and precipitation projections available for climate change impacts in the U.S. The gridded dataset covers the continental United States, southern Canada and northern Mexico at one-eighth degree resolution and Alaska at one-half degree resolution. The high-resolution projections produced by this work have been rigorously quality-controlled for both errors and biases in the global climate and statistical downscaling models. We also calculated projected future changes in a broad range of impact-relevant indicators, from seasonal temperature to extreme precipitation days. The results of the error and bias tests and the indicator calculations are made available as part of this database. Additional information and raw data from this dataset can be found here: http://cida.usgs.gov/thredds/catalog.html Before using this dataset, please review the material summarized here: https://my.usgs.gov/confluence/display/GeoDataPortal/2014/04/16/Notice%3A+Evaluation+of+Maurer+gridded+observational+datasets+and+their+impacts+on+downscaled+products Note that the CONUS temperature and precipitation data were split into two sub datasets in January 2015. This was done because the precipitation data uses a slightly different longitude axis than the temperature data.

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The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The American Indian/Alaska Native/Native Hawaiian (AIANNH) Areas Shapefile includes the following legal entities: federally recognized American Indian reservations and off-reservation trust land areas, state-recognized American Indian reservations, and Hawaiian home lands (HHLs). The statistical entities included are Alaska Native village statistical areas (ANVSAs), Oklahoma tribal statistical areas (OTSAs), tribal designated statistical areas (TDSAs), and state designated tribal statistical areas (SDTSAs). Joint use areas are also included in this shapefile refer to areas that are administered jointly and/or claimed by two or more American Indian tribes. The Census Bureau designates both legal and statistical joint use areas as unique geographic entities for the purpose of presenting statistical data. Note that tribal subdivisions and Alaska Native Regional Corporations (ANRCs) are additional types of American Indian/Alaska Native areas stored by the Census Bureau, but are displayed in separate shapefiles because of how they fall within the Census Bureau's geographic hierarchy. The State of Hawaii's Office of Hawaiian Home Lands provides the legal boundaries for the HHLs. The boundaries for ANVSAs, OTSAs, and TDSAs were delineated for the 2010 Census through the Tribal Statistical Areas Program (TSAP) by participants from the federally recognized tribal governments. The Bureau of Indian Affairs (BIA) within the U.S. Department of the Interior (DOI) provides the list of federally recognized tribes and only provides legal boundary information when the tribes need supporting records, if a boundary is based on treaty or another document that is historical or open to legal interpretation, or when another tribal, state, or local government challenges the depiction of a reservation or off-reservation trust land. The boundaries for federally recognized American Indian reservations and off-reservation trust lands are as of January 1, 2013, as reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries for state-recognized American Indian reservations and for SDTSAs were delineated by a state governor-appointed liaisons for the 2010 Census through the State American Indian Reservation Program and TSAP respectively.

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Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme, orthographic imagery, is packaged in a separate NFIP Metadata Profile): cadastral, geodetic control, governmental unit, transportation, general structures, hydrography (water areas and lines). These data include an encoding of the geographic extent of the features and a minimal number of attributes needed to identify and describe the features. (Source: Circular A-16, p. 13)

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The purpose of this study was to provide an in-depth look at rapes and attempted rapes in the United States. Part 1 of the collection offers data on rape victims and contains variables regarding the characteristics of the crime, such as the setting, the r

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The Global Hourly Summaries are simple indicators of observational normals which include climatic data summarizations and frequency distributions. These typically are statistical analyses of station data over 5-, 10-, 20-, 30-year or longer time periods. In a GIS map service, the results of these calculations are represented by a given symbology set for different statistical criteria and observation type. Having the ability to modify the symbology "on-the-fly" is a useful tool in the analysis of station trends, accuracy, and regional or localized variances. The summaries are computed from the global surface hourly dataset. This dataset totaling over 350 gigabytes is comprised of 40 different types of weather observations with 20,000 stations worldwide. NCDC and the U.S. Navy have developed these value added products in the form of hourly summaries from many of these observations. These data are a subset of the Integrated Surface Hourly dataset (DSI-3505) (C00532).

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<p>The goal of the Protein Colloidal Aggregation project is to understand the underlying cause of several major diseases, including Alzheimer’s, Parkinson’s, and chronic traumatic encephalopathy. These diseases all occur when protein molecules undergo a peculiar and irreversible process in which they aggregate to form tiny fibers of a unique material called amyloid, which the body cannot remove. Despite enormous investment in research, the fundamental physiochemical mechanism of these diseases remains poorly understood. </p><p>Based on initial studies using atomic force microscopy (AFM), we theorized that the aggregation of proteins in these diseases is driven instead by colloidal interactions, the same forces that govern the behavior of nanoscale particles in the colloidal suspensions we encounter every day, such as paint, milk, and clouds.</p><p>Our theory is being validated by the evidence. For many years, NASA has been heavily involved in research into the structure of proteins and their assembly into crystals, and in studying the colloidal interactions and aggregation of nanoscale particles. To date, however, NASA’s colloid research has involved only nonbiological materials. But now we are bridging these two fields by studying the colloidal aggregation of proteins.</p>

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In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to make informed decisions about this issue. The research carried out as part of the study described here was designed to help refine nutrient budgets for Chesapeake Bay by characterizing submarine groundwater flow and discharge of groundwater beneath part of the mainstem and a major tributary, the Potomac River Estuary.

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This archive contains 234 projections of monthly BCSD CMIP5 projections of precipitation and monthly means of daily-average, daily maximum and daily minimum temperature over the contiguous United States. For more information visit http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/

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New England City and Town Area (NECTA) Divisions subdivide a NECTA containing a single core urban area that has a population of at least 2.5 million to form smaller groupings of cities and towns. NECTA Divisions are defined by the Office of Management and Budget OMB) and consist of a main city or town that represents an employment center, plus adjacent cities and towns associated with the main city or town through commuting ties. Each NECTA Division must contain a total population of 100,000 or more. Because NECTA Divisions represent subdivisions of larger NECTAs, it is not appropriate to rank or compare NECTA Divisions with NECTAs. Not all NECTAs with urban areas of this size will contain NECTA Divisions. The NECTA Divisions boundaries are those defined by OMB based on the 2010 Census and published in 2013.

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Utility level retail sales of electricity and associated revenue in 2009. Organized by reporting month, state, and by end-use sector, i.e., residential, commercial, industrial, and transportation. Based on Form EIA-826 data.

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Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, flight lines of standard density (1.4 meter ground sample distance) data were collected over areas in Brazoria County, TX (approximately 1428 square miles). Multiple returns were recorded for each laser pulse along with an intensity value for each return. The data acquisition occurred in 6 missions between April 9, 2006, April 16, 2006, April 17, 2006, and May 11, 2006 through May 13, 2006. The data was collected by Sanborn Mapping Company, Inc. for the Texas Water Development Board (TWDB) and the Federal Emergency Management Agency (FEMA).

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This dataset represents a historical repository of all the numerical data from the smartgrid.gov website condensed into spreadsheets to enable analysis of the data. Below are a couple of things worth noting: * The data visible on the smartgrid.gov website is dynamic. As new data is submitted by the utilities, it is validated, and then gets published to the website. So the smartgrid.gov website always contains the most current data. * The attached spreadsheets are a quarterly, static "snapshots" of the data from the smartgrid.gov website. So if there is a discrepancy between values in this dataset and the smartgrid.gov website; the website numbers always represent the most current data. * The cost data in this dataset is the summation of project and cost share values reported by the utilities. (In other words, the cost data is the sum of federal dollars spent plus cost share dollars spent by the recipient utility.) * Some of the values visible on the website are aggregations of the values in the quarterly data summary spreadsheets.

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This data set is a polygon coverage created in ARC/INFO that represents the generalized thickness of the Madison Limestone and Englewood Formation, Black Hills, South Dakota. The thickness of the Madison Limestone and Englewood Formation was determined by substracting the elevation of the top of the Deadwood Formation from the elevation of the top of the Madison Limestone. The elevations for the tops of the formations were determined from geologic logs for wells drilled as of 1998. The thickness coverage contains polygons that have single integer values representing a range of thickness.

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These ESRI shape files are of National Park Service tract and boundary data that was created by the Land Resources Division. Tracts are numbered and created by the regional cartographic staff at the Land Resources Program Centers and are associated to the Land Status Maps. This data should be used to display properties that NPS owns and properties that NPS may have some type of interest such as scenic easements or right of ways.

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Provides the basic information for general acute care hospital buildings such as height, number of stories, the building code used to design the building and year it was completed. The data is sorted by counties and cities. Structural Performance Categories (SPC ratings) are also provided. SPC ratings range from 1 to 5 with SPC 1 assigned to buildings that may be at risk of collapse during a strong earthquake and SPC 5 assigned to buildings reasonably capable of providing services to the public following a strong earthquake. Where SPC ratings have not been confirmed by the Office of Statewide Health, Planning and Development (OSHPD) yet, the rating index is followed by 's'. A URL for the building webpage in OSHPD/FDD eServices Portal is also provided to view projects related to any building.

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When ice accretes on a wing or other aerodynamic surface, it can produce extremely complex shapes. These are comprised of well-known shapes such as horns and feathers but also include other shapes such as the scallops that are associated with swept wing icing. The development of the larger ice shapes is generally believed to be influenced or built up from smaller scale surface structures such as roughness elements which can grow into the precursors of feathers or scallops seen on larger swept wing ice accretions. Feathers and scallops are often comprised of complex interlocking geometries that can contain a large number of voids. Hence it is important to characterize the geometries of these ice shapes, not only to ensure an adequate representation of the geometry for subsequent aerodynamic effects studies but also to provide data to validate icing codes, understand the basic physics involved with the ice accretion, and provide a basis for modeling the ice accretion. To address the above issue, we propose to use an X-ray computed tomography (CT) imaging method to demonstrate that X-ray CT scanning can be used to measure 3D ice features of the form seen in aircraft ice accretions. We also propose to conduct a preliminary trade/design analysis to establish directions for a more detailed Phase II study that would address specific recommendations to integrate X-ray CT imaging with icing wind tunnels which can be used at NASA Glenn and commercial aerospace companies. It is anticipated that the proposed imaging method could provide a radically new way to visualize and characterize extremely complex 3D ice shapes.

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Information on donor contributions through the 2012 Combined Federal Campaign by local campaign. Data includes information on the number of donors, campaign costs, payroll deduction contributions, and recipient organizations

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This data set contains the outlines for historic (i.e., relinquished or inactive) federal oil and gas leases in the Alaska OCS Region through sale 193. They represent a close approximation, but might not be the exact coordinates for those leases. For the official coordinates please refer to the OPD or SOBD for the lease. ALSO NOTE: older leases were done on a NAD 27 grid, and their lease coordinates will not change as long as the lease remains active. Although the NAD 27 leases have been projected to NAD 83 for inclusion in this file, when plotted on the current NAD 83 leasing grid, they will not appear to "line up", because the NAD 83 grids represents a complete re-grid and not a re-projection of the old NAD 27 grid. All current leasing, starting with Sale 144 in September 1996 has been done on the NAD 83 grid.

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CoastWatch is a nationwide National Oceanic and Atmospheric Administration (NOAA) program within which the Great Lakes Environmental Research Laboratory (GLERL) functions as the Great Lakes regional node. In this capacity, GLERL obtains, produces, and delivers environmental data and products for near real-time observation of the Great Lakes to support environmental science, decision making, and supporting research. This is achieved by providing access to near real-time and retrospective satellite observations and in-situ Great Lakes data. The goals and objectives of the CoastWatch Great Lakes Program directly support NOAA's statutory responsibilities in estuarine and marine science living marine resource protection, and ecosystem monitoring and management. The CoastWatch node at GLERL provides clients including Federal, state, and local agencies, academic institutions, commercial/industries and the public, both within and outside of the Great Lakes region, with access to near real-time satellite observations and in-situ data for the Great Lakes. CoastWatch data are used in a variety of ways, including near real-time observation and tracking of algal blooms, plumes, ice cover, wind, water intake temperatures at fish hatcheries, two and three dimensional modeling of Great Lakes physical parameters such as wave height and currents damage assessment modeling, research, and educational and recreational activities. In addition, through a cooperative project with Michigan Sea Grant, Great Lakes CoastWatch satellite-derived surface temperature imagery is contoured and made available via Michigan State Sea Grant's web site. Great Lakes CoastWatch data and products benefit riparians as well as commercial and recreational users. GLERL is currently receiving a product suite of 33 enhanced digital images including satellite-derived surface temperature (Fig. 1.1), visible and near-infrared reflectance, brightness temperatures, cloud masks, and satellite/solar zenith angle data from the NOAA/AVHRR (Advanced Very High Resolution Radiometer) series of satellites as well as GOES (Geostationary Operational Environmental Satellites) visible, near infrared, and water vapor data. These products are acquired by GLERL from NOAA's National Environmental Satellite, Data, and Information Service (NESDIS) on a daily schedule via Internet. In addition, MODIS true color 250m resolution imagery (Fig. 1.2) of each Great Lake (received near real-time from the Space Science and Engineering Center at the University of Wisconsin), in-situ and modeled data, including marine and meteorological observations, buoy observations, water level gauge measurements from NOAA's National Ocean Service, and Great Lakes Surface Environmental Analysis (GLSEA) composite charts (Fig. 1.3), are routinely acquired or produced, stored, and made available to Great Lakes CoastWatch data users. Great Lakes Forecasting system (nowcast and forecast) products are also available to CoastWatch data users. Near real-time AVHRR satellite data for the past 2 weeks are available at GLERL, and access to a retrospective archive that begins in 1990 is available via an Internet link to the NOAA CoastWatch Active Access System at the NESDIS Satellite Active Archive.