Skip to main content
Advanced Search

Filters: Tags: Climate change (X) > Categories: Data (X) > Types: Raster (X)

83 results (18ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
Current binomial (presence/absence) model of Brown Creeper (Certhia americana) using a Boosted Regression Tree model (Hastie & Tibshirani 2000) informed by breeding season avian point count data, modeled vegetation types, and climate data from PRISM (Daly et al. 2004) averaged for the years 1971-2000.
thumbnail
Mean modeled snow-water-equivalent (meters) on February 20, the date of peak basin-integrated mean modeled snow-water-equivalent (meters) for the T4 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
thumbnail
The percentage difference between mean modeled snow-water-equivalent (meters) on April 1 for the reference (1989-2011) climate period and mean modeled snow-water-equivalent on April 1 for the T4 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
thumbnail
The absolute difference between mean modeled snow-water-equivalent on March 28 for the reference period and mean modeled snow-water-equivalent on February 20 for the T4P10 climate change scenario, which are the dates of peak basin-integrated SWE for each period, respectively.Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.
thumbnail
The percentage difference between mean modeled snow-water-equivalent (meters) on April 1 for the reference (1989-2011) climate period and mean modeled snow-water-equivalent on April 1 for the T2 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T2 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
This project gallery includes all project reports and associated assessment materials, including interactive and downloadable connectivity and climate datasets for the project " Creating Practitioner-driven, Science-based Plans for Connectivity Conservation in a Changing Climate: A Collaborative Assessment of Climate-Connectivity Needs in the Washington-British Columbia Transboundary Region".
thumbnail
Mean modeled snow-water-equivalent (meters) on March 13, the date of peak basin-integrated mean modeled snow-water-equivalent (meters) for the T2 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T2 scenario: the observed historical (reference period) meteorology is perturbed by adding +2oC to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
thumbnail
Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability...
thumbnail
The Arizona Game and Fish Department (AGFD) recognizes the need for a strong data foundation to inform science-based decisions for fisheries management at a watershed level. In preparation for a shift towards comprehensive watershed-scale planning, AGFD is developing a fisheries data management system with an initial focus on compiling and formatting several hundred thousand fish survey and stocking records. Fish data will be integrated within a Geographic Information System (GIS) by georeferencing observations to an existing national spatial framework (National Hydrography Dataset), which will allow for broader transferability to watersheds shared with neighboring states, creating a seamless layer not limited by...
thumbnail
The absolute difference between mean modeled snow-water-equivalent (meters) on April 1 for the reference (1989-2011) climate period and mean modeled snow-water-equivalent on April 1 for the T4P10 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.
Future density (birds per hectare) model of Brown Creeper (Certhia americana) using a Boosted Regression Tree model (Hastie & Tibshirani 2000) informed by breeding season avian point count data, modeled vegetation types, and climate data from the Canadian Regional Climate Model (CRCM) with boundary conditions driven by the Community Climate System Model (CCSM) averaged for the years 2041-2070 and available from http://www.narccap.ucar.edu/.
thumbnail
Current probability of occurrence model of Scrub Jay (Aphelocoma californica) using a Boosted Regression Tree model (Hastie & Tibshirani 2000) informed by breeding season avian point count data, modeled vegetation types, and climate data from PRISM (Daly et al. 2004) averaged for the years 1971-2000.
Future density (birds per hectare) model of Brown Creeper (Certhia americana) using a Boosted Regression Tree model (Hastie & Tibshirani 2000) informed by breeding season avian point count data, modeled vegetation types, and climate data from the Regional Climate Model v3 (RCM3) with boundary conditions driven by the Third Generation Coupled Global Climate Model (CGCM3) averaged for the years 2041-2070 and available from http://www.narccap.ucar.edu/.
thumbnail
The absolute difference between mean modeled snow-water-equivalent on March 28 for the reference period and mean modeled snow-water-equivalent on March 13 for the T2P10 climate change scenario, which are the dates of peak basin-integrated SWE for each period, respectively. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T2P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.
thumbnail
These two datasets represent a normalized least-cost corridor mosaic (see WHCWG 2010 and McRae and Kavanagh 2011) calculated using (1) temperature gradients and a landscape integrity resistance raster, or (2) temperature gradients only, following the climate gradient linkage-modeling methods outlined in Nuñez (2011), using an adapted version of the Linkage Mapper software (McRae and Kavanagh 2011). This GIS dataset is one of several climate connectivity analyses produced by Tristan Nuñez for a Master's thesis (Nuñez 2011). The dataset was produced in part to assist the Climate Change Subgroup of the Washington Wildlife Habitat Connectivity Working Group (WHCWG). The core areas in the map lie in Washington State...
thumbnail
The absolute difference between mean modeled snow-water-equivalent on March 28 for the reference period and mean modeled snow-water-equivalent on March 13 for the T2P10 climate change scenario, which are the dates of peak basin-integrated SWE for each period, respectively. Reference period: the period 1989 – 2009 for the McKenzie River Basin domain, and 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T2P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data...
thumbnail
Mean modeled snow-water-equivalent (meters) on April 1 for the T2 climate change scenario. T2 scenario: the observed historical (reference period) meteorology is perturbed by adding +2°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
thumbnail
The absolute difference between mean modeled snow-water-equivalent on March 28 for the reference period and mean modeled snow-water-equivalent on February 20 for the T4 climate change scenario, which are the dates of peak basin-integrated SWE for each period, respectively. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record in the reference period meteorology, and this data is then used as input to the model.
thumbnail
Mean modeled snow-water-equivalent (meters) on February 20, the date of peak basin-integrated mean modeled snow-water-equivalent (meters) for the T4P10 climate change scenario. Reference period: the period 1989 – 2011 for the Upper Deschutes River Basin domain, for which observed historical meteorology is used for model input. T4P10 scenario: the observed historical (reference period) meteorology is perturbed by adding +4°C to each daily temperature record, and +10% precipitation to each daily precipitation record in the reference period meteorology, and this data is then used as input to the model.
thumbnail
Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. This dataset presents projections of historic and future fire probability for the southcentral U.S. using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM, Guyette et al., 2012). Climate data from 1900-1929 and projected climate data for 2040-2069 and 2070-2099 were used as model inputs to the Physical Chemistry Fire Frequency Model (Guyette et al. 2012) to estimate fire probability. Baseline and future time period data are from three global climate models (GCMs): CGCM, GFDL, and HadCM3. The nine associated data sets (tiffs) represent estimated change in mean fire probability...


map background search result map search result map Current probability of occurrence model of Scrub Jay (Aphelocoma californica) using a Boosted Regression Tree model A Landscape Approach for Fisheries Database Compilation and Predictive Modeling (Not listed in the LCC Science Catalog due to Desert LCC co-funding and catalog administering) Modeled snow-water-equivalent, absolute difference between seasonal peak historical and projected values under T2p10 climate change scenario, McKenzie River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected April 1 values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected April 1 values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T2P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Normalized least-corridor mosaic using temperature gradients and landscape integrity resistance Fire probability for 1900-1929 using CGCM baseline climate values Fire probability for 1900-1929 using GFDL baseline climate values Modeled snow-water-equivalent, absolute difference in historical and projected April 1 values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, percent difference between historical and projected April 1 values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected April 1 values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T2P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference in historical and projected seasonal peak values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T2 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, projected seasonal peak values under T4P10 climate change scenario, Upper Deschutes River Basin, Oregon [full and clipped versions] Modeled snow-water-equivalent, absolute difference between seasonal peak historical and projected values under T2p10 climate change scenario, McKenzie River Basin, Oregon [full and clipped versions] A Landscape Approach for Fisheries Database Compilation and Predictive Modeling (Not listed in the LCC Science Catalog due to Desert LCC co-funding and catalog administering) Normalized least-corridor mosaic using temperature gradients and landscape integrity resistance Current probability of occurrence model of Scrub Jay (Aphelocoma californica) using a Boosted Regression Tree model Fire probability for 1900-1929 using GFDL baseline climate values Fire probability for 1900-1929 using CGCM baseline climate values