Skip to main content
USGS - science for a changing world
Advanced Search

Filters: Categories: Data (X) > Types: Citation (X)

9,151 results (50ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
In February 2016 the University of Washington in cooperation with the U.S. Geological Survey, Pacific Coastal and Marine Science Center (USGS, PCMSC) collected multibeam bathymetry and acoustic backscatter data in the Catalina Basin aboard the University of Washington's Research Vessel Thomas G. Thompson. Data was collected using a Kongsberg EM300 multibeam echosounder hull-mounted to the 274-foot R/V Thomas G. Thompson. The USGS, PCMSC processed these data and produced a series of bathymetric surfaces and acoustic backscatter images for scientific research purposes. A 25-m bathymetric surface produced from this work was merged with publically available multibeam bathymetry data as well as 2015, 2016, and 2017 multibeam...
thumbnail
Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
thumbnail
Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
thumbnail
Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
thumbnail
Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
thumbnail
Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
thumbnail
Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
thumbnail
Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
thumbnail
This data set consists of monthly averages of soil and litter properties. Rows are grouped in the following order: year, month, vegetation type, plot ID. Within a single month five plots were sampled within each of the 2 vegetation types (10 plots total). Columns F+ represent individual measurements.
thumbnail
This inventory was originally created by Gorum and others (2014) describing the landslides triggered by a sequence of earthquakes, with the largest being the M 6.2 17 km N of Puerto Aisen, Chile earthquake that occurred on 21 April 2007 at 23:45:56 UTC. Care should be taken when comparing with other inventories because different authors use different mapping techniques. This inventory includes landslides triggered by a sequence of earthquakes rather than a single mainshock. Please check the author methods summary and the original data source for more information on these details and to confirm the viability of this inventory for your specific use. With the exception of the data from USGS sources, the inventory...
thumbnail
This part of the data release provides the U.S. Geological Survey (USGS), Pacific Coastal and Marine Science Center (PCMSC) 2007 bathymetry data collected in Skagit Bay Washington that is provided as a 1-m resolution TIFF image, as well as a 1-m resolution shaded-relief TIFF image. FGDC metadata is also provided. In 2004, 2005, 2007, and 2010 the USGS, PCMSC collected bathymetry and acoustic backscatter data in Skagit Bay, Washington using an interferometric bathymetric sidescan-sonar system mounded to the USGS R/V Parke Snavely and the USGS R/V Karluk. The research was conducted in coordination with the Swinomish Indian Tribal Community, Skagit River System Cooperative, Skagit Watershed Council, Puget Sound Nearshore...
thumbnail
This release contains Active Layer Thickness (ALT) and Organic Layer Thickness (OLT) measurements measured along transects in Alaska, 2015. Site condition information in terms of wildfire burns is also included.
thumbnail
Separate data for floodplain elevation and bathymetry were collected on the Upper Mississippi River System (UMRS) by the US Army Corps of Engineers (USACE), Upper Mississippi River Restoration (UMRR) Program. While many information needs can be met by using these data separately, in many cases seamless elevation data across the river and its floodplain are needed. This seamless elevation surface was generated by merging lidar (i.e., floodplain elevation) and bathymetry data. Merging the data required special processing in the areas of transition between the two sources of data.
thumbnail
In 1991, the U.S. Geological Survey (USGS) began a study of more than 50 major river basins across the Nation as part of the National Water-Quality Assessment (NAWQA) project of the National Water-Quality Program. One of the major goals of the NAWQA project is to determine how water-quality conditions change over time. To support that goal, long-term consistent and comparable monitoring has been conducted on streams and rivers throughout the Nation. Outside of the NAWQA project, the USGS and other Federal, State, and local agencies also have collected long-term water-quality data to support their own assessments of changing water-quality conditions. Data from these multiple sources have been combined to support...
thumbnail
This data table contains mean decomposition rates and mean carbon:nitrogen ratios for different litter types buried in 7 marshes during 2015. Note that C:N data are repeated for low and high marsh areas at each site in the table. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6
thumbnail
This data set contains decomposition rates for litter of Salicornia pacifica, Distichlis spicata, and Deschampsia cespitosa buried at 7 tidal marsh sites in 2015. Sediment organic matter values were collected at a subset of sites. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6


map background search result map search result map Water-quality and streamflow datasets used in the Weighted Regressions on Time, Discharge, and Season (WRTDS) models to determine trends in the Nation’s rivers and streams, 1972-2012(output) Permafrost Soil Measurements; Alaska, 2015 UMRR La Grange Topobathy Gorum and others (2014) Digital Orthorectified Aerial Image of Cottonwood Lake Study Area Wetland T2 from 1983 Decomposition rates and carbon:nitrogen ratios for different litter types, 2015 Litter Decomposition Rates, 2015 Digital Orthorectified Aerial Image of Cottonwood Lake Study Area Wetland P11 from 2007 Digital Orthorectified Aerial Image of Cottonwood Lake Study Area Wetlands P1, T1, and T3 from 2009 Digital Orthorectified Aerial Image of Cottonwood Lake Study Area Wetlands P6 and P7 from 2011 EFFECTS OF FLOOD INUNDATION AND INVASION BY Phalaris arundinacea ON NITROGEN CYCLING IN AN UPPER MISSISSIPPI RIVER FLOODPLAIN FOREST Merged multibeam bathymetry--northern portion of the Southern California Continental Borderland High-resolution bathymetry data collected in 2007 in Skagit Bay, Washington Precipitation (Proportion July - Sep) - 2020-2050 - RCP8.5 - Min Temperature (Mean: Annual) - 2020-2050 - RCP8.5 - Min Precipitation (Proportion May - Oct) - 1980-2010 Precipitation (Proportion May - Oct) - 2070-2100 - RCP4.5 - Min Precipitation (Proportion May - Oct) - 2020-2050 - RCP4.5 - Min Precipitation (Mean: Apr - June) - 2070-2100 - RCP4.5 - Max Precipitation (Mean: Dec - Mar) - 2020-2050 - RCP4.5 - Min Digital Orthorectified Aerial Image of Cottonwood Lake Study Area Wetland T2 from 1983 Digital Orthorectified Aerial Image of Cottonwood Lake Study Area Wetlands P1, T1, and T3 from 2009 Digital Orthorectified Aerial Image of Cottonwood Lake Study Area Wetlands P6 and P7 from 2011 Digital Orthorectified Aerial Image of Cottonwood Lake Study Area Wetland P11 from 2007 High-resolution bathymetry data collected in 2007 in Skagit Bay, Washington Gorum and others (2014) UMRR La Grange Topobathy Merged multibeam bathymetry--northern portion of the Southern California Continental Borderland Permafrost Soil Measurements; Alaska, 2015 Decomposition rates and carbon:nitrogen ratios for different litter types, 2015 Litter Decomposition Rates, 2015 Precipitation (Proportion July - Sep) - 2020-2050 - RCP8.5 - Min Temperature (Mean: Annual) - 2020-2050 - RCP8.5 - Min Precipitation (Proportion May - Oct) - 1980-2010 Precipitation (Proportion May - Oct) - 2070-2100 - RCP4.5 - Min Precipitation (Proportion May - Oct) - 2020-2050 - RCP4.5 - Min Precipitation (Mean: Apr - June) - 2070-2100 - RCP4.5 - Max Precipitation (Mean: Dec - Mar) - 2020-2050 - RCP4.5 - Min Water-quality and streamflow datasets used in the Weighted Regressions on Time, Discharge, and Season (WRTDS) models to determine trends in the Nation’s rivers and streams, 1972-2012(output)