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Alldata:3D Land Mapping + (The overall objective of the project is to … The overall objective of the project is to combine radar and lidar remote sensing to characterize the forested landscapes in 3D. The science products generated by Simard and collaborators have four main components:1 Global scale mapping of canopy height and biomass at 1km spatial resolution.2 Improving Shuttle Radar Topography Mission (SRTM) elevation dataset using ICESat's Geoscience Laser Altimeter System (GLAS).3 High spatial resolution mapping of canopy height and biomass using polarimeteric synthetic aperture radar interferometry (polinSAR) and LiDAR.4 Mapping of mangrove forests canopy height, biomass, productivity and assessment of vulnerability to anthropogenic activity and sea level change.thropogenic activity and sea level change.)
Alldata:R-ArcticNet + (This comprehensive river discharge databas … This comprehensive river discharge database covers the entire pan-Arctic drainage system. The collection comprises data from 9138 gauges and contains monthly river discharge data extending from the 1890s (for four Canadian and five Russian gauges) through the early 1990s, but the majority of data was collected between 1960 and 2001. The pan-Arctic drainage region covers a land area of approximately 21 million km2 and drains into the Arctic Ocean as well as Hudson Bay, James Bay, and the Northern Bering Strait. The collection also includes the Yukon and Anadyr River basins. Most of the drainage basins in the database are greater than 15,000 km2; however, the collection includes all available gauge data from Canada and Russia. Data from gauges measuring large drainage areas are of greatest interest to the regional, continental, and global-scale scientific community for modeling purposes. Individual station data are accessible through a graphical interface, or as tab-delimited ASCII text. Tab-delimited ASCII data are also compiled by hydrological region and as a single file for the complete data set.s a single file for the complete data set.)
Alldata:National Climatic Data Center HDSS Access System + (This data portal, operated by the National … This data portal, operated by the National Oceanic and Atmospheric Administration (NOAA) and the National Climatic Data Center (NCDC), contains archives of weather radar data (Doppler radar: NEXRAD), satellite coverage, and additional surface and marine data. These additional surface and marine data comprise historical forecasts and analyses, as well as the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) that covers three centuries of global ocean-atmosphere data, including 2x2 and (since 1960) 1x1 degree gridded data sets.A tutorial for retrieving radar data is here:http://www.ncdc.noaa.gov/oa/radar/nxhastutorial.html.ncdc.noaa.gov/oa/radar/nxhastutorial.html)
Alldata:Sea Ice Concentrations NSIDC + (This data set is generated from brightness … This data set is generated from brightness temperature data derived from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and Defense Meteorological Satellite Program (DMSP) -F8, -F11 and -F13 Special Sensor Microwave/Imager (SSM/I) radiances at a grid cell size of 25 x 25 km. The data are provided in the polar stereographic projection.This product is designed to provide a consistent time series of sea ice concentrations (the fraction, or percentage, of ocean area covered by sea ice) spanning the coverage of several passive microwave instruments. To aid in this goal, sea ice algorithm coefficients are changed to reduce differences in sea ice extent and area as estimated using the SMMR and SSM/I sensors. The data are generated using the NASA Team algorithm developed by the Oceans and Ice Branch, Laboratory for Hydrospheric Processes at NASA Goddard Space Flight Center (GSFC).These data include gridded daily (every other day for SMMR data) and monthly averaged sea ice concentrations for both the north and south polar regions. Two types of data are provided: final data and preliminary data. Final data are produced at GSFC about once per year, with roughly a one-year latency, and include data since 26 October 1978. Final data are produced from SMMR brightness temperature data processed at NASA GSFC and SSM/I brightness temperature data processed at the National Snow and Ice Data Center (NSIDC). Preliminary data are produced at NSIDC approximately every three months (quarterly), using SSM/I data acquired from Remote Sensing Systems, Inc. (RSS), and include roughly the most recent three to twelve months of processed data.Data are scaled and stored as one-byte integers in flat binary arrays.s one-byte integers in flat binary arrays.)
Alldata:Clara Orru - measured data of a degradational sand-gravel laboratory experiment + (This data set is related to the degradational sand-gravel laoratory experiment described in http://dx.doi.org/10.1002/2016WR018938. It was created by Clara Orru, Delft University of Technology.)
Alldata:Great Bay, NH - BBL Data June 2011 + (This data set provides acoustic measuremen … This data set provides acoustic measurements of the bottom boundary layer in a tidal current over flat muddy-sand bed. Observations made with Nortek Vectrino Profiler over the lowest 2.5 cm of the water column with a 1 mm resolution. Observations were made in June of 2011 just after slack tide during a flood tidal flow. Please contact Diane Foster of the University of New Hampshire with any questions (diane.foster@unh.edu).References:Wengrove, M. E., & Foster, D. L. (2014). Field evidence of the viscous sublayer in a tidally forced developing boundary layer. Geophysical Research Letters, 41(14), 5084-5090.Wengrove, M. E., Foster, D. L., Kalnejais, L. H., Percuoco, V., & Lippmann, T. C. (2015). Field and laboratory observations of bed stress and associated nutrient release in a tidal estuary. Estuarine, Coastal and Shelf Science, 161, 11-24. Estuarine, Coastal and Shelf Science, 161, 11-24.)
Alldata:Permafrost Temperatures, Alaska + (This dataset consists of borehole temperat … This dataset consists of borehole temperature measurements acquired in permafrost regions of arctic Alaska between 1950 and 1988 by the U.S. Geological Survey. A large number of the 87 sites (boreholes) represented in this dataset are deep enough to penetrate the base of permafrost.nough to penetrate the base of permafrost.)

(This dataset consists of borehole temperature measurements acquired in p)

Alldata:Nearshore Oceanographic Observations at Drew Point, Alaska, Summers 2009 and 2010 + (This dataset includes observations of wate … This dataset includes observations of water level, water temperature, and wave field collected in 2009 and 2010 near Drew Point, AK by investigators Anderson, Overeem, and Wobus, with help from Adam LeWinter. This data was used in a publication published in 2014 by Barnhart et al.Please see the file README.txt that accompanies the data files. Barnhart, K. R., R. S. Anderson, I. Overeem, C. Wobus, G. D. Clow, and F. E. Urban (2014), Modeling erosion of ice-rich permafrost bluffs along the Alaskan Beaufort Sea coast, Journal of Geophysical Research Earth Surface, 119, doi:10.1002/2013JF002845.Five files are included in this dataset: 1. README.txt (this document)2. TidbitWaterTemperature_2009.txt 3. WaveLogger2_2009.txt 4. WaveLoggerTemperature_2009 5. Levelogger_2010.txt 6. WaveLogger_2010.txtevelogger_2010.txt 6. WaveLogger_2010.txt)
Alldata:LUSoils v.1 + (This dataset links human land use and land … This dataset links human land use and land cover types from the Land-Use Harmonization (LUH2) dataset (Lawrence et al., 2016) to four hydrologic soil groups from 850 to 2015 derived from the SoilGrids250m soils dataset (Hengl et al., 2017). These groups represent sandy soils (hydrologic group A) consisting of texture classes sand, sandy-loam and loamy sand; silty soils (hydrologic group B) consisting of loam, silty-loam and silt; a mixed sand-silt-clay soils (hydrologic group C); and clayey soils (hydrologic group D) represented by clay, sandy-clay, clay-loam, silty-clay, and silt-clay-loam texture classes from the SoilGrids250m dataset. This dataset makes it possible to better link LULCs to soil types typically used for these activities potentially improving the simulation of water, energy and biogeochemical processes in Earth System Models. Additionally, it lays the foundation for simulating LULC impacts on soils that have different vulnerabilities and responses to human uses of soils.ties and responses to human uses of soils.)
Alldata:OSCAR + (This project is developing a processing sy … This project is developing a processing system and data center to provide operational ocean surface velocity fields from satellite altimeter and vector wind data.The regional focus will be the tropical Pacific, where we will demonstrate the value for a variety of users, specifically fisheries management and recruitment, monitoring debris drift, larvae drift, oil spills, fronts and eddies, as well as on-going large scale ENSO monitoring, diagnostics and prediction. We will encourage additional uses in search and rescue, naval and maritime operations. The data will be subjected to extensive validation and error analysis, and applied to various ocean, climate and dynamic basic research problems. The user base derives from the NOAA CoastWatch and climate prediction programs, the broad research community, the Navy's operational ocean analysis program, and other civilian uses. The end product is to leave in place a turnkey system running at NOAA/NESDIS, with an established user clientele and easy internet data access.The method to derive surface currents with satellite altimeter and scatterometer data is the outcome of several years NASA sponsored research.The proposed project will transition that capability to operational oceanographic applications. The end product will be velocity maps updated daily, 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. The team consists of private non-profit, educational and government partners with broad experience and familiarity with the data, and the scientific and technical issues. Two Partners are the original developers of the surface current derivation techniques, and two are closely tied to satellite data sources and primary processing centers. Others represent NOAA/NESDIS, Climate Prediction Center, CoastWatch, NMFS and the Navy to evaluate uses and applications.he Navy to evaluate uses and applications.)
Alldata:WaveWatch III^TM + (WAVEWATCH III™ (Tolman 1997, 1999a, 2009) … WAVEWATCH III™ (Tolman 1997, 1999a, 2009) is a third generation wave model developed at NOAA/NCEP in the spirit of the WAM model (WAMDIG 1988, Komen et al. 1994). It is a further development of the model WAVEWATCH, as developed at Delft University of Technology (Tolman 1989, 1991a) and WAVEWATCH II, developed at NASA, Goddard Space Flight Center (e.g., Tolman 1992). WAVEWATCH III™, however, differs from its predecessors in many important points such as the governing equations, the model structure, the numerical methods and the physical parameterizations. Furthermore, with model version 3.14, WAVEWATCH III™ is evolving from a wave model into a wave modeling framework, which allows for easy development of additional physical and numerical approaches to wave modeling.WAVEWATCH III™ solves the random phase spectral action density balance equation for wavenumber-direction spectra. The implicit assumption of this equation is that properties of medium (water depth and current) as well as the wave field itself vary on time and space scales that are much larger than the variation scales of a single wave. With version 3.14 some source term options for extremely shallow water (surf zone) have been included, as well as wetting and drying of grid points. Whereas the surf-zone physics implemented so far are still fairly rudimentary, it does imply that the wave model can now be applied to arbitrary shallow water.now be applied to arbitrary shallow water.)
Alldata:AI&ML Challenge Dataset + (We present data for use with ML, dealing w … We present data for use with ML, dealing with the sediment/rock substrates of the NE USA Continental Margin. The pointwise Labelled Data from seabed observations should be spatially extended over the entire area in an intelligent way. To aid that, environmental Feature Layers can be employed to train any chosen Machine Learning method. The trained ML model is then extended across all the vacant areas. The result predicts what the seabed is made of, so that survey operations (including research) can be planned, or biogeochemical budgets can be calculated. The idea of the Challenge Dataset is to permit people - researchers and students - to experiment with their own Machine Learning algorithms and data-preparation adjustments to achieve the BEST POSSIBLE mapping over the area. Metrics on the uncertainties should also be computed. For the time being the mappings are in terms of mud/sand/gravel, rock exposure, and carbonate and organic carbon contents. See the Powerpoint file in the Zipfile for further instructions.e in the Zipfile for further instructions.)
Alldata:World Ocean atlas + (World Ocean Atlas 2009 (WOA09) is a set of … World Ocean Atlas 2009 (WOA09) is a set of objectively analyzed (1° grid) climatological fields of in situ temperature, salinity, dissolved oxygen, Apparent Oxygen Utilization (AOU), percent oxygen saturation, phosphate, silicate, and nitrate at standard depth levels for annual, seasonal, and monthly compositing periods for the World Ocean. It also includes associated statistical fields of observed oceanographic profile data interpolated to standard depth levels on both 1° and 5° grids .ard depth levels on both 1° and 5° grids .)
Alldata:UNPD + (World Population Prospects: The 2008 Revis … World Population Prospects: The 2008 Revision Population Database from the United Nations Population Division.The preparation of each new revision of the official population estimates and projections of the United Nations involves two distinct processes: (a) the incorporation of all new and relevant information regarding the past demographic dynamics of the population of each country or area of the world; and (b) the formulation of detailed assumptions about the future paths of fertility, mortality and international migration. The data sources used and the methods applied in revising past estimates of demographic indicators (i.e., those referring to 1950-2010) are presented online and in volume III of World Population Prospects: The 2008 Revision (forthcoming).The future population of each country is projected starting with an estimated population for 1 July 2010. Because population data are not necessarily available for that date, the 2010 estimate is derived from the most recent population data available for each country, obtained usually from a population census or a population register, projected to 2010 using all available data on fertility, mortality and international migration trends between the reference date of the population data available and 1 July 2010. In cases where data on the components of population change relative to the past 5 or 10 years are not available, estimated demographic trends are projections based on the most recent available data. Population data from all sources are evaluated for completeness, accuracy and consistency, and adjusted as necessary.To project the population until 2050, the United Nations Population Division uses assumptions regarding future trends in fertility, mortality and international migration. Because future trends cannot be known with certainty, a number of projection variants are produced. The following paragraphs summarize the main assumptions underlying the derivation of demographic indicators for the period starting in 2010 and ending in 2050. A more detailed description of the different assumptions will be available in volume III of World Population Prospects: The 2008 Revision (forthcoming)The 2008 Revision includes eight projection variants. The eight variants are: low; medium; high; constant-fertility; instant-replacement-fertility; constant-mortality; no change (constant-fertility and constant-mortality); and zero-migration. The World Population Prospects Highlights focuses on the medium variant of the 2008 Revision, and results from the first four variants are available on-line.first four variants are available on-line.)