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Ken Ferschweiler (CBI) used climate data from the PRISM group (Chris Daly, Oregon State University) at 4kmx4km spatial grain across the conterminous USA to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling and created anomalies from the Hadley CM3 General Circulation Model (GCM) run through the A2 emission scenario (SRES - special report on emission scenarios published in 2000). To run the MAPSS model (Neilson 1995), average monthly precipitation values were calculated for the period 2045-2060. This dataset shows the standard deviation of the annual precipitation for that period.
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Ken Ferschweiler (CBI) used climate data from the PRISM group (Chris Daly, Oregon State University) at 4kmx4km spatial grain across the conterminous USA to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling and created anomalies from the Hadley CM3 General Circulation Model (GCM) run through the A2 emission scenario (SRES - special report on emission scenarios published in 2000). To run the MAPSS model (Neilson 1995), average monthly temperatures were calculated for the period 2045-2060. This dataset shows the standard deviation of the annual mean temperature for that period.
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Ken Ferschweiler (CBI) used climate data from the PRISM group (Chris Daly, Oregon State University) at 4kmx4km spatial grain across the conterminous USA to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling and created anomalies from the Hadley CM3 General Circulation Model (GCM) run through the A2 emission scenario (SRES - special report on emission scenarios published in 2000). To run the MAPSS model (Neilson 1995), average monthly precipitation values were calculated for the period 2045-2060. This dataset shows the mean anomaly (difference) in the annual precipitation for that period with respect to the 1971-2000 baseline period.
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Global climate models (GCMs) are numerically complex, computationally intensive, physics-based research tools used to simulate our planet’s inter-connected climate system. In addition to improving the scientific understanding of how the large-scale climate system works, GCM simulations of past and future climate conditions can be useful in applied research contexts. When seeking to apply information from global-scale climate projections to address local- and regional-scale climate questions, GCM-generated datasets often undergo statistical post-processing generally known as statistical downscaling (hereafter, SD). There are many different SD techniques, with all using information from observations to address GCM...
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Ken Ferschweiler (CBI) used climate data from the PRISM group (Chris Daly, Oregon State University) at 4kmx4km spatial grain across the conterminous USA to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling and created anomalies from the Hadley CM3 General Circulation Model (GCM) run through the A2 emission scenario (SRES - special report on emission scenarios published in 2000). To run the MAPSS model (Neilson 1995), average monthly temperatures were calculated for the period 2045-2060. This dataset shows the mean anomaly (difference) in the annual mean temperature for that period with respect to the 1971-2000 baseline period.
Abstract (from http://link.springer.com/article/10.1007/s10584-016-1598-0): Empirical statistical downscaling (ESD) methods seek to refine global climate model (GCM) outputs via processes that glean information from a combination of observations and GCM simulations. They aim to create value-added climate projections by reducing biases and adding finer spatial detail. Analysis techniques, such as cross-validation, allow assessments of how well ESD methods meet these goals during observational periods. However, the extent to which an ESD method’s skill might differ when applied to future climate projections cannot be assessed readily in the same manner. Here we present a “perfect model” experimental design that quantifies...
The MC2 model projects an overall increase in carbon capture in conterminous United States during the 21st century while also simulating a rise in fire causing much carbon loss. Carbon sequestration in soils is critical to prevent carbon losses from future disturbances, and we show that natural ecosystems store more carbon belowground than managed systems do. Natural and human-caused disturbances affect soil processes that shape ecosystem recovery and competitive interactions between native, exotics, and climate refugees. Tomorrow's carbon budgets will depend on how land use, natural disturbances, and climate variability will interact and affect the balance between carbon capture and release.
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Ken Ferschweiler (CBI) used climate data from the PRISM group (Chris Daly, Oregon State University) at 4kmx4km spatial grain across the conterminous USA to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling and created anomalies from the Hadley CM3 General Circulation Model (GCM) run through the A2 emission scenario (SRES - special report on emission scenarios published in 2000). To run the MAPSS model (Neilson 1995), average monthly temperatures were calculated for the period 2045-2060. This dataset shows the change in leaf area index simulated by MAPSS compared to the historical period (1968-1999) based on PRISM climate data.
This fact sheet provides highlights from a comprehensive U.S. Geological Survey report that evaluates six widely used downscaled climate projections covering the southeastern United States and recommends best practices for use of downscaled datasets for ecological modeling and decision-making.
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Ken Ferschweiler (CBI) used climate data from the PRISM group (Chris Daly, Oregon State University) at 4kmx4km spatial grain across the conterminous USA to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling and created anomalies from the Hadley CM3 General Circulation Model (GCM) run through the A2 emission scenario (SRES - special report on emission scenarios published in 2000). To run the MAPSS model (Neilson 1995), average monthly temperatures were calculated for the period 2045-2060. This dataset shows the change in runoff simulated by MAPSS compared to the historical period (1968-1999) based on PRISM climate data.
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Global climate models (GCMs) are numerically complex, computationally intensive, physics-based research tools used to simulate our planet’s inter-connected climate system. In addition to improving the scientific understanding of how the large-scale climate system works, GCM simulations of past and future climate conditions can be useful in applied research contexts. When seeking to apply information from global-scale climate projections to address local- and regional-scale climate questions, GCM-generated datasets often undergo statistical post-processing generally known as statistical downscaling (hereafter, SD). There are many different SD techniques, with all using information from observations to address GCM...
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This dataset represents projected survey and managed species probability of occupancy for the climate of 2061-2090, averaged from the occurrence probabilities of 130 survey and managed species. The survey and manage species are rare localized species of concern under the Northwest Forest plan, consisting of 75 species of fungi, 21 species of lichen, 10 species of bryophytes, 8 species of vascular plants, 12 species of mollusks, 2 species of amphibians, one mammal, and one bird. Climate data were drawn from three representative climate projections: lowest warming (GCM GISS_ER with IPCC storyline B1), moderate warming (GCM ECHAM5 SRES with storyline A2), and highest warming (GCM IPSL_CM4 with storyline A2). In Carroll...
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This dataset represents projected survey and manage species probability of occupancy for the climate of 2011-2040, averaged from the occurrence probabilities of 130 survey and manage species. The survey and manage species are rare localized species of concern under the Northwest Forest plan, consisting of 75 species of fungi, 21 species of lichen, 10 species of bryophytes, 8 species of vascular plants, 12 species of mollusks, 2 species of amphibians, one mammal, and one bird. Climate data were drawn from three representative climate projections: lowest warming (GCM GISS_ER with IPCC storyline B1), moderate warming (GCM ECHAM5 SRES with storyline A2), and highest warming (GCM IPSL_CM4 with storyline A2). In Carroll...
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The California Basin Characterization Model (CA-BCM 2014) dataset provides historical and projected climate and hydrologic surfaces for the region that encompasses the state of California and all the streams that flow into it (California hydrologic region ). The CA-BCM 2014 applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270-m grid. The model has been calibrated using a total of 159 relatively unimpaired watersheds for the California region. The historical data is based on 800m PRISM data spatially downscaled to 270 m using the gradient-inverse distance squared approach (GIDS), and the projected climate surfaces include five CMIP-3 (GFDL,...
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This dataset represents projected spotted owl habitat probability of occupancy for the climate of 2061-2090 based on the mean habitat occupancy predictions from three representative climate projections: lowest warming (GCM GISS_ER with IPCC storyline B1), moderate warming (GCM ECHAM5 SRES with storyline A2), and highest warming (GCM IPSL_CM4 with storyline A2). In Carroll and others (in prep.), we evaluate how a system of reserves can be made resilient to climate change. First, we assess how well the NFP's reserve network currently protects habitat for spotted owl and rare "Survey and Manage" species. Then, we assess how these species will fare under climate change. Our results suggest that the spotted owl acts...
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The Regional Climate Downloader (RCD) is a web application that can be used to visualize and download climate data. The RCD uses the Web Mapping Service (WMS) that is built into the Thredds Data Server , (see Disclaimer and Terms of Use ) that allows users to map and download monthly average data for over 60 surface variables generated by the Dynamical Downscaling project. The time coverage of these simulations ranges from 1968 to 2100, depending on the region of simulation and the driving GCM. Decadal, monthly and daily data are available for the Dynamical Downscaling project. Other datasets such as CIG are also available from within RCD. Data are available in NetCDF format.
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This dataset represents predicted spotted owl habitat probability of occupancy for the current climate. In Carroll and others (in prep.), we evaluate how a system of reserves can be made resilient to climate change. First, we assess how well the NFP's reserve network currently protects habitat for spotted owl and rare "Survey and Manage" species. Then, we assess how these species will fare under climate change. Our results suggest that the spotted owl acts as fairly good "umbrella" species for protecting localized species. We identify additional coarse-scale priority areas for localized species, protection of which would allow achievement of the goals of the Survey and Manage program while reducing the resources...
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This dataset represents projected spotted owl habitat probability of occupancy for the climate of 2011-2040 based on the mean habitat occupancy predictions from three representative climate projections: lowest warming (GCM GISS_ER with IPCC storyline B1), moderate warming (GCM ECHAM5 SRES with storyline A2), and highest warming (GCM IPSL_CM4 with storyline A2). In Carroll and others (in prep.), we evaluate how a system of reserves can be made resilient to climate change. First, we assess how well the NFP's reserve network currently protects habitat for spotted owl and rare "Survey and Manage" species. Then, we assess how these species will fare under climate change. Our results suggest that the spotted owl acts...


map background search result map search result map USGS Regional Climate Downloader Change in Leaf Area Index (2045-2060) Simulated by MAPSS using HadCM3 GCM under A2 scenario (Western USA) Change in Runoff (2045-2060) Simulated by MAPSS using HadCM3 GCM under A2 scenario (Western USA) Standard Deviation of Annual Temperature (2045-2060) from HadCM3 GCM under A2 scenario (Western USA) Standard Deviation of Annual Precipitation (2045-2060) from HadCM3 GCM under A2 scenario (Western USA) Average Annual Precipitation Anomaly (2045-2060) from HadCM3 GCM under A2 scenario (Western USA) Average Annual Temperature Anomaly (2045-2060) from HadCM3 GCM under A2 scenario (Western USA) Pacific Northwest Predicted Spotted Owl Habitat Occupancy for Current Climate Pacific Northwest Projected Spotted Owl Habitat Occupancy for 2061-2090 Pacific Northwest Projected Spotted Owl Habitat Occupancy for 2011-2040 Pacific Northwest Predicted Survey and Manage Species Occupancy for 2061-2090 Pacific Northwest Predicted Survey and Manage Species Occupancy for 2011-2040 California Basin Characterization Model Downscaled Climate and Hydrology Data Integration Workshop in Support of the Coastal Temperate Rainforest of Southeast Alaska and British Columbia South Central Climate Projections Evaluation Project (C-PrEP) South Central Climate Projections Evaluation Project (C-PrEP) Data Integration Workshop in Support of the Coastal Temperate Rainforest of Southeast Alaska and British Columbia Pacific Northwest Predicted Spotted Owl Habitat Occupancy for Current Climate Pacific Northwest Projected Spotted Owl Habitat Occupancy for 2061-2090 Pacific Northwest Projected Spotted Owl Habitat Occupancy for 2011-2040 Pacific Northwest Predicted Survey and Manage Species Occupancy for 2061-2090 Pacific Northwest Predicted Survey and Manage Species Occupancy for 2011-2040 California Basin Characterization Model Downscaled Climate and Hydrology South Central Climate Projections Evaluation Project (C-PrEP) South Central Climate Projections Evaluation Project (C-PrEP) Change in Leaf Area Index (2045-2060) Simulated by MAPSS using HadCM3 GCM under A2 scenario (Western USA) Change in Runoff (2045-2060) Simulated by MAPSS using HadCM3 GCM under A2 scenario (Western USA) Standard Deviation of Annual Temperature (2045-2060) from HadCM3 GCM under A2 scenario (Western USA) Standard Deviation of Annual Precipitation (2045-2060) from HadCM3 GCM under A2 scenario (Western USA) Average Annual Precipitation Anomaly (2045-2060) from HadCM3 GCM under A2 scenario (Western USA) Average Annual Temperature Anomaly (2045-2060) from HadCM3 GCM under A2 scenario (Western USA) USGS Regional Climate Downloader