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For his MS thesis, Brendan Rogers used climate data from the PRISM group (Chris Daly, Oregon State University) at a 30arc second (800m) spatial grain across the western 2/3 of the states of Oregon and Washington to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling to create anomalies from three General Circulation Models (CSIRO Mk3, MIROC 3.2 medres, and Hadley CM 3), each run through three CO2 emission scenarios (SRES B1, A1B, and A2).
For his MS thesis, Brendan Rogers used climate data from the PRISM group (Chris Daly, Oregon State University) at a 30arc second (800m) spatial grain across the western 2/3 of the states of Oregon and Washington to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling to create anomalies from three General Circulation Models (CSIRO Mk3, MIROC 3.2 medres, and Hadley CM 3), each run through three CO2 emission scenarios (SRES B1, A1B, and A2).
For his MS thesis, Brendan Rogers used climate data from the PRISM group (Chris Daly, Oregon State University) at a 30arc second (800m) spatial grain across the western 2/3 of the states of Oregon and Washington to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling to create anomalies from three General Circulation Models (CSIRO Mk3, MIROC 3.2 medres, and Hadley CM 3), each run through three CO2 emission scenarios (SRES B1, A1B, and A2).
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through...
For his MS thesis, Brendan Rogers used climate data from the PRISM group (Chris Daly, Oregon State University) at a 30arc second (800m) spatial grain across the western 2/3 of the states of Oregon and Washington to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling to create anomalies from three General Circulation Models (CSIRO Mk3, MIROC 3.2 medres, and Hadley CM 3), each run through three CO2 emission scenarios (SRES B1, A1B, and A2).
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through statistical...
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through statistical...
For his MS thesis, Brendan Rogers used climate data from the PRISM group (Chris Daly, Oregon State University) at a 30arc second (800m) spatial grain across the western 2/3 of the states of Oregon and Washington (USA) to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling to create anomalies from three General Circulation Models (CSIRO Mk3, MIROC 3.2 medres, and Hadley CM 3), each run through three CO2 emission scenarios (SRES B1, A1B, and A2).
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through statistical...
For his MS thesis, Brendan Rogers used climate data from the PRISM group (Chris Daly, Oregon State University) at a 30arc second (800m) spatial grain across the western 2/3 of the states of Oregon and Washington (USA) to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling to create anomalies from three General Circulation Models (CSIRO Mk3, MIROC 3.2 medres, and Hadley CM 3), each run through three CO2 emission scenarios (SRES B1, A1B, and A2).
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through statistical...
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through...
For his MS thesis, Brendan Rogers used climate data from the PRISM group (Chris Daly, Oregon State University) at a 30arc second (800m) spatial grain across the western 2/3 of the states of Oregon and Washington to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling to create anomalies from three General Circulation Models (CSIRO Mk3, MIROC 3.2 medres, and Hadley CM 3), each run through three CO2 emission scenarios (SRES B1, A1B, and A2).
For his MS thesis, Brendan Rogers used climate data from the PRISM group (Chris Daly, Oregon State University) at a 30arc second (800m) spatial grain across the western 2/3 of the states of Oregon and Washington (USA) to generate a climatology or baseline. He then created future climate change scenarios using statistical downscaling to create anomalies from three General Circulation Models (CSIRO Mk3, MIROC 3.2 medres, and Hadley CM 3), each run through three CO2 emission scenarios (SRES B1, A1B, and A2).
A combination of remote sensing and ecosystem modeling is used to examine the trends in NEP and net ecosystem carbon balance (NECB) in this region over the 1985–2007 period, with particular attention to land ownership since management now differs widely between public and private forestland. In the late 1980s, forestland in both ownership classes was subject to high rates of harvesting, and consequently the land was a carbon source (i.e. had a negative NECB). After the policy driven reduction in the harvest level, public forestland became a large carbon sink driven in part by increasing NEP whereas private forestland was close to carbon neutral.
Annual average wind resource potential of the northwestern United States at a 50 meter height. Available from the National Renewable Energy Laboratory (NREL) at http://www.nrel.gov/renewable_resources/ . This dataset was last updated on 1/24/2011.
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through...
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through statistical...
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through statistical...
For his MS thesis, Brendan Rogers used the vegetation model MC1 to simulate vegetation dynamics, associated carbon and nitrogen cycle, water budget and wild fire impacts across the western 2/3 of the states of Oregon and Washington using climate input data from the PRISM group (Chris Daly, OSU) at a 30arc second (800m) spatial grain. The model was run from 1895 to 2100 assuming that nitrogen demand from the plants was always met so that the nitrogen concentrations in various plant parts never dropped below their minimum reported values. A CO2 enhancement effect increased productivity and water use efficiency as the atmospheric CO2 concentration increased. Future climate change scenarios were generated through statistical...
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