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Information on the nature and distribution of permafrost is critical to assessing the response of Arctic ecosystems to climate change, because thawing permafrost under a warming climate will cause thaw settlement and affect micro-topography, surface water redistribution and groundwater movement, soil carbon balance, trace gas emissions, vegetation changes, and habitat use. While a small-scale regional permafrost map is available, as well as information from numerous site-specific large-scale mapping projects, landscape-level mapping of permafrost characteristics is needed for regional modeling and climate impact assessments. The project addresses this need by: (1) compiling existing soil/permafrost data from available...
The Integrated Ecosystem Model (IEM) for Alaska and Northwest Canada Project integrated existing models of vegetation, disturbance, and permafrost into one complete ecosystem model for the state of Alaska and Northwest Canada.The final synchronized model will integrate existing climate, vegetation, disturbance, hydrology, and permafrost models to improve understanding of potential landscape, habitat and ecosystem change. The project’s (September 1, 2011 through August 31, 2016) primary goal was to develop the IEM modeling framework to integrate the driving components for and the interactions among disturbance regimes, permafrost dynamics, hydrology, and vegetation succession/migration for Alaska and Northwest Canada....
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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The Integrated Ecosystem Model is designed to help resource managers understand the nature and expected rate of landscape change. Maps and other products generated by the IEM will illustrate how arctic and boreal landscapes are expected to alter due to climate-driven changes to vegetation, disturbance, hydrology, and permafrost. The products will also provide resource managers with an understanding of the uncertainty in the expected outcomes.
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This dataset includes Snow Free Date(sfdy) for northern Alaska in GeoTiff format, covering the years 1980-2012. Snow Free Date is defined as day of the end of the core snow period(day of year). The core snow season is defined to be the longest period of continuous snow cover in each year. The dataset was generated by the Arctic LCC SNOWDATA: Snow Datasets for Arctic Terrestrial Applications project.“Day-of-year” (doy) output is expressed in Ordinal dates (“1” on 1 January, and “365” on 31 December). Dates have not been corrected for leap years. This output is appropriate for display purposes, as it is readily interpreted as calendar day of year. It is not recommended as input for analysis, as it may produce incorrect...
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: AIR TEMPERATURE, AIR TEMPERATURE, ALBEDO, ALBEDO, Academics & scientific researchers, All tags...
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This dataset includes Snow Depth(snod) for northern Alaska in GeoTiff format, covering the years 1980-2012. Snow Depth is defined as depth on 1 March(m). The dataset was generated by the Arctic LCC SNOWDATA: Snow Datasets for Arctic Terrestrial Applications project.The dataset is delivered in the ZIP archive file format. Each year is output in a separate GeoTiff file, where the year is indicated by the filename.Over the last 20 years, under a variety of NOAA, NSF, and NASA research programs, a snow-evolution modeling system has been developed that includes the MicroMet micrometeorological model, the SnowModel snow-process model, and the SnowAssim data assimilation model. These modeling tools can be thought of as...
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: AIR TEMPERATURE, AIR TEMPERATURE, ALBEDO, ALBEDO, Academics & scientific researchers, All tags...
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Information on the nature and distribution of permafrost is critical to assessing the response of Arctic ecosystems to climate change, because thawing permafrost under a warming climate will cause thaw settlement and affect micro-topography, surface water redistribution and groundwater movement, soil carbon balance, trace gas emissions, vegetation changes, and habitat use. While a small-scale regional permafrost map is available, as well as information from numerous site-specific large-scale mapping projects, landscape-level mapping of permafrost characteristics is needed for regional modeling and climate impact assessments. The project addresses this need by: (1) compiling existing soil/permafrost data from available...
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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We mosaicked twelve LandSat-8 OLI satellite images taken during the summer of 2014, which were used in an object based image analysis (OBIA) to classify the landscape. We mapped seventeen of the most dominant geomorphic land cover classes on the ACP: (1) Coastal saline waters, (2) Large lakes, (3) Medium lakes, (4) Small lakes, (5) Ponds, (6) Rivers, (7) Meadows, (8) Coalescent low-center polygons, (9) Low-center polygons, (10) Flat-center polygons, (11) High-center polygons, (12) Drained slope, (13) Sandy barrens, (14) Sand dunes, (15) Riparian shrub, (16) Ice, and (17) Urban (i.e. towns and roads). Mapped products were validated with an array of oblique aerial/ground based photography (Jorgenson et al., 2011)...
The ALCC has asked the U.S. Institute for Environmental Conflict Resolution (U.S. Institute) to assist them in engaging a third-party neutral facilitator who can work with the steering committee to identify key landscape scale resource management needs common to many of the ALCC partners. The overall goals of this project are twofold. One is to identify key future landscape scale resource management and science needs that are common to many of the ALCC partners, and in doing so, increase understanding of future landscape scale information needs among the ALCC steering committee members.
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This pilot project has initiated a long-term integrated modeling project that aims todevelop a dynamically linked model framework focused on climate driven changes tovegetation, disturbance, hydrology, and permafrost, and their interactions and feedbacks.This pilot phase has developed a conceptual framework for linking current state-of-thesciencemodels of ecosystem processes in Alaska – ALFRESCO, TEM, GIPL-1 – and theprimary processes of vegetation, disturbance, hydrology, and permafrost that theysimulate. A framework that dynamically links these models has been defined and primaryinput datasets required by the models have been developed.
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Information on the nature and distribution of permafrost is critical to assessing the response of Arctic ecosystems to climate change, because thawing permafrost under a warming climate will cause thaw settlement and affect micro-topography, surface water redistribution and groundwater movement, soil carbon balance, trace gas emissions, vegetation changes, and habitat use. While a small-scale regional permafrost map is available, as well as information from numerous site-specific large-scale mapping projects, landscape-level mapping of permafrost characteristics is needed for regional modeling and climate impact assessments. The project addresses this need by: (1) compiling existing soil/permafrost data from available...
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Information on the nature and distribution of permafrost is critical to assessing the response of Arctic ecosystems to climate change, because thawing permafrost under a warming climate will cause thaw settlement and affect micro-topography, surface water redistribution and groundwater movement, soil carbon balance, trace gas emissions, vegetation changes, and habitat use. While a small-scale regional permafrost map is available, as well as information from numerous site-specific large-scale mapping projects, landscape-level mapping of permafrost characteristics is needed for regional modeling and climate impact assessments. The project addresses this need by: (1) compiling existing soil/permafrost data from available...
Permafrost is a unique characteristic of polar regions and high mountains and is fundamentalto geomorphic processes and ecological development in permafrost-affected environments.Because permafrost impedes drainage and ice-rich permafrost settles upon thawing, degradationof permafrost in response to climate change will have large consequences for tundra and borealecosystems (Osterkamp 2005, Jorgenson and Osterkamp 2005, Shur and Osterkamp 2007,Jorgenson et al. 2010, 2013). Thawing permafrost affects surface hydrology by impoundingwater in subsiding areas and enhances drainage of upland areas. Changes in soil drainage altersoil carbon dynamics, habitats for vegetation and wildlife, and emissions of greenhouse gases(Ping...
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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These raster datasets represent historical stand age. The last four digits of the file name specifies the year represented by the raster. For example a file named Age_years_historical_1990.tif represents the year 1990. Cell values represent the age of vegetation in years since last fire, with zero (0) indicating burned area in that year. Files from years 1860-2006 use a variety of historical datasets for Boreal ALFRESCO model spin up and calibration to most closely match historical wildfire dynamics.
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These raster datasets are output from the Geophysical Institute Permafrost Lab (GIPL) model and represents simulated mean annual ground temperature (MAGT) in Celsius, averaged across a decade, at the base of active layer or at the base of the seasonally frozen soil column. These data were generated by driving the GIPL model with a composite of five GCM model outputs for the A1B emissions scenario. The file name specifies the decade the raster represents. For example, a file named MAGT_1980_1989.tif represents the decade spanning 1980-1989. Cell values represent simulated mean annual ground temperature (degree C) at the base of the active layer (for areas with permafrost) or at the base of the soil column that is...
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This dataset includes Snow Up Date(sudt) for northern Alaska in GeoTiff format, covering the years 1980-2012. Snow Up Date is defined as day of the start of the core snow period(day of simulation). The core snow season is defined to be the longest period of continuous snow cover in each year. The dataset was generated by the Arctic LCC SNOWDATA: Snow Datasets for Arctic Terrestrial Applications project.The simulation period runs from 1 September – 31 August. “Day-of-simulation” takes the value of “1” on 1 September, “123” on 1 January, and “365” on 31 August. “Day-of-simulation” files should be used for analysis (trend, mean, etc.).The dataset is delivered in the ZIP archive file format. Each year is output in a...
Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: AIR TEMPERATURE, AIR TEMPERATURE, ALBEDO, ALBEDO, Academics & scientific researchers, All tags...


map background search result map search result map Permafrost Database Development, Characterization, and Mapping for Northern Alaska SNOWDATA GeoTIFF Annual Snow Free Date (year) SNOWDATA GeoTIFF Annual Snow Depth SNOWDATA GeoTIFF Annual Snow Up Date Alaskan Arctic Coastal Plain Polygonal Geomorphology Map Development and Application of an Integrated Ecosystem Model for Alaska Simulated Mean Annual Ground Temperature Integrated Ecosystem Model Reports IEM-CSC Factsheet with Supplement, 2015 Historical Stand Age 1980-1989 Historical Stand Age 1870-1879 Historical Stand Age 1940-1949 Historical Stand Age 1900-1909 Historical Stand Age 1960-1969 Historical Stand Age 1910-1919 Permafrost Database Development, Characterization, and Mapping for Northern Alaska Permafrost Database Development, Characterization, and Mapping for Northern Alaska Permafrost Database Development, Characterization, and Mapping for Northern Alaska Permafrost Characterization and Mapping for Northern Alaska Final Report Alaskan Arctic Coastal Plain Polygonal Geomorphology Map Permafrost Database Development, Characterization, and Mapping for Northern Alaska Permafrost Database Development, Characterization, and Mapping for Northern Alaska Permafrost Database Development, Characterization, and Mapping for Northern Alaska Permafrost Database Development, Characterization, and Mapping for Northern Alaska Permafrost Characterization and Mapping for Northern Alaska Final Report SNOWDATA GeoTIFF Annual Snow Free Date (year) SNOWDATA GeoTIFF Annual Snow Depth SNOWDATA GeoTIFF Annual Snow Up Date Simulated Mean Annual Ground Temperature Integrated Ecosystem Model Reports IEM-CSC Factsheet with Supplement, 2015 Historical Stand Age 1980-1989 Historical Stand Age 1870-1879 Historical Stand Age 1940-1949 Historical Stand Age 1900-1909 Historical Stand Age 1960-1969 Historical Stand Age 1910-1919