Filters: Tags: Climatology (X)
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Interannual differences in the water quality of Anvil Lake, WI, were examined to determine how water level and climate affect the hydrodynamics and trophic state of shallow lakes, and their importance compared to anthropogenic changes in the watershed. To determine how changes in water level may affect these processes, the General Lake Model (GLM) was used to simulate how the lake’s thermal structure should change in response to changes in water level using R. This dataset includes the data inputs to the GLM model and the direct outputs from the model. Model Calibration (GLM_CalibrationZ); Simulation of with Deep Lake and Cold Weather (GLM_Deep_Cold_SimulationZ); Simulation of with Deep Lake and Hot Weather (GLM_Deep_Hot_SimulationZ);...
This data release provides a set of Hydrological Simulation Program--Fortran (HSPF) model files representing 5 EPA-selected future climate change scenarios for each of two river basins: Taunton and Sudbury, in Massachusetts. Output from these models are intended for use as input to EPA Watershed Management Optimization Support Tool (WMOST) modeling. Climate scenarios, based on 2036-2065 change from 1975-2004 Representative Concentration Pathways (RCP) 4.5 and 8.5, model effects of air temperature and precipitation changes (in degrees F for air temperature, in percent for precipitation) made to the input historical meteorological time series 1975-2004. Taunton meteorological data is from T.F. Green Airport and the...
Types: Citation;
Tags: Climatology,
Sudbury,
Taunton,
USGS Science Data Catalog (SDC),
Water Resources,
The Sea Ice Index provides a quick look at sea ice changes in spatial and historical context and gives a consistent, up-to-date source of sea ice extent and sea ice concentration values and images. The NSIDC Near-Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations and the Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I Passive Microwave Data data sets are used to generate the monthly records of sea ice extent and sea ice concentration for the Arctic and Antarctica from satellite passive microwave data. Data files tabulate monthly mean extent and area, in millions of square kilometers, by year for a given month. Plots of monthly sea ice extent anomalies with trend lines and significance intervals...
The Sea Ice Index provides a quick look at sea ice changes in spatial and historical context and gives a consistent, up-to-date source of sea ice extent and sea ice concentration values and images. The NSIDC Near-Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations and the Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I Passive Microwave Data data sets are used to generate the monthly records of sea ice extent and sea ice concentration for the Arctic and Antarctica from satellite passive microwave data. Data files tabulate monthly mean extent and area, in millions of square kilometers, by year for a given month. Plots of monthly sea ice extent anomalies with trend lines and significance intervals...
The Sea Ice Index provides a quick look at sea ice changes in spatial and historical context and gives a consistent, up-to-date source of sea ice extent and sea ice concentration values and images. The NSIDC Near-Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations and the Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I Passive Microwave Data data sets are used to generate the monthly records of sea ice extent and sea ice concentration for the Arctic and Antarctica from satellite passive microwave data. Data files tabulate monthly mean extent and area, in millions of square kilometers, by year for a given month. Plots of monthly sea ice extent anomalies with trend lines and significance intervals...
The Sea Ice Index provides a quick look at sea ice changes in spatial and historical context and gives a consistent, up-to-date source of sea ice extent and sea ice concentration values and images. The NSIDC Near-Real-Time DMSP SSM/I Daily Polar Gridded Sea Ice Concentrations and the Sea Ice Concentrations from Nimbus-7 SSMR and DMSP SSM/I Passive Microwave Data data sets are used to generate the monthly records of sea ice extent and sea ice concentration for the Arctic and Antarctica from satellite passive microwave data. Data files tabulate monthly mean extent and area, in millions of square kilometers, by year for a given month. Plots of monthly sea ice extent anomalies with trend lines and significance intervals...
Soil frost measurements have been made at Sleepers River Research Watershed starting in 1983. Measurements were made by U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory from 1983 to 1993, followed by the U.S. Geological Survey from 1993 to the present. Measurements started at 5 sites and has increased to 10 sites. Sites range in elevation from 225 to 670 meters and are in a mix of field and forest types. Soil frost measurements are made with tubes filled with methylene blue solution; on freezing, the methylene blue remains in the liquid phase, yielding clear ice that marks the depth of soil frost (Ricard and others, 1976). Soil frost measurements typically are made 2 to 4 times a month...
Categories: Data;
Tags: Climatology,
Danville, Vermont,
USGS Science Data Catalog (SDC),
Water Resources,
biota,
The data release consists of a single NetCDF file with results from a suite of ice sheet model simulations. We ran with Community Ice Sheet Model (CISM2) with input from models used in the Palaeoclimate Modelling Intercomparison 3 (PMIP3). The NetCDF file contains output from model year 50,000 for a limited number of variables to keep the file size reasonably small. This subset of variables are the ones we focus our analysis and paper on.
Categories: Data Release - Revised;
Tags: North America,
USGS Science Data Catalog (SDC),
air temperature,
climatology,
glaciation,
Monthly Standardize Precipitation Evapotranspiration Index (SPEI), Daily soil-water potential (MPa) and soil temperature (degree C) data for plots from SageSuccess. The SageSuccess Project is a joint effort between USGS, BLM, and FWS to understand how to establish big sagebrush and ultimately restore functioning sagebrush ecosystems. Improving the success of land management treatments to restore sagebrush-steppe is important for reducing the long-term impacts of rangeland fire on sage-grouse and over 350 other wildlife species that use these habitats.
These data represent simulated soil temperature and moisture conditions for current climate, and for future climate represented by all available climate models at two time periods during the 21st century. These data were used to: 1) quantify the direction and magnitude of expected changes in several measures of soil temperature and soil moisture, including the key variables used to distinguish the regimes used in the R and R categories; 2) assess how these changes will impact the geographic distribution of soil temperature and moisture regimes; and 3) explore the implications for using R and R categories for estimating future ecosystem resilience and resistance.
Some of the NOS rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal Mean Annual Ground Temperature at 1 Meter Depth (°C) for the decades 2010-2019, 2020-2029, and 2060-2069 at 2km spatial resolution. It represents the A2 emissions scenario and the spatial extent is the NOS REA study area.
Some of the NOS rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal average January temperature (in °C) for the decades 2010-2019, 2020-2029, and 2060-2069 at 771x771 meter spatial resolution. The file represents a decadal mean calculated from monthly totals, using the A2 emissions scenario. The spatial extent is clipped to the NOS REA...
Some of the NOS rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal average May temperature (in °C) for the decades 2010-2019, 2020-2029, and 2060-2069 at 771x771 meter spatial resolution. The file represents a decadal mean calculated from monthly totals, using the A2 emissions scenario. The spatial extent is clipped to the NOS REA study...
Some of the NOS rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal average of spring (March, April, May) total precipitation (in millimeters) for the decades 2010-2019, 2020-2029, and 2060-2069 at 771x771 meter spatial resolution. The file represents a decadal mean of seasonal totals calculated from monthly totals, using the A2 emissions...
Some of the CYR rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - The Relative Flammability raster is a spatial representation of the total number of times each pixel within the Central Yukon REA boundary burned in 1,000 simulations of the Alaska Frame-Based Ecosystem Code (ALFRESCO) model. Pixel counts of simulated burns from 200 runs each of five downscaled Global Climate Models (cccma_cgcm3_1,...
Some of the YKL rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal mean Day of Thaw (in ordinal dates) for the decade 2060-2069 at 771x771 meter spatial resolution. Day of Thaw approximates when the running mean rises above 0°C. Although raster values represent ordinal dates, the values 0 and 365 are special classes. A value of 0 indicates...
This shapefile includes projections of annual area burned, fire return interval, and percent forest (current decade only) for the current (2010s), near-term (2020s) and long-term (2050s and 2060s) decades, for the A2 emissions scenario, for 3rd level HUCs within the YKL REA study area. Values were obtained by running 100 repetitions of the Alaska Frame-Based Ecosystem Code (ALFRESCO) model for the top five performing global climate models in the Arctic at a 1x1 km resolution. These outputs were then averaged together to determine the composite, 5 model average, the decades of interest extracted, and the resulting table exported as a shapefile. For background on ALFRESCO, please refer to: Is Alaska's Boreal Forest...
Some of the YKL rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal average of winter (December, January, February) total precipitation (in millimeters) for the decade 2050-2059 at 771x771 meter spatial resolution. The file represents a decadal mean of seasonal totals calculated from monthly totals, using the A1B emissions scenario. The...
Some of the YKL rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal average of winter (December, January, February) total precipitation (in millimeters) for the decade 2050-2059 at 771x771 meter spatial resolution. The file represents a decadal mean of seasonal totals calculated from monthly totals, using the A2 emissions scenario. The...
Some of the YKL rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal average of summer (June, July, August) total precipitation (in millimeters) for the decade 2050-2059 at 771x771 meter spatial resolution. The file represents a decadal mean of seasonal totals calculated from monthly totals, using the A2 emissions scenario. The spatial extent...
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