Filters: Tags: projections (X)
108 results (96ms)
Filters
Date Range
Extensions Types Contacts
Categories Tag Types
|
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 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 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).
Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan 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...
Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan 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...
Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan 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...
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 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...
Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan 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...
Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan 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...
Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan 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...
Soil residual water corresponds to the model variable "total streamflow." In the model MC1, this is calculated (in cm of water) as the water flowing through the soil profile below the last soil layer (streamflow), water leached into the subsoil (baseflow) and also includes runoff. The output is presented here as a monthly average. Soil residual water is part of the model output from Brendan Rogers' MS thesis work. Brendan 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...
OPTIONS model- post processing- of structural stages, stand age, and Northern Spotted Owl (NSO) habitat index at years 0, 10, 20, 30, 40, 50, 100 for the Roseburg Sustained Yield Unit (SYU) portion of the Western Oregon Plan Revision (WOPR) area. *See Appendix R of the Western Oregon Plan Revision Proposed Resource Managemnt Plan for further description.BLM (Bureau of Land Management) WOPR (Western Oregon Plan Revision) WOPR Theme Group: OPT (Options) WOPR Purpose: O (Options) GLUA: General Land Use Allocations PRMP: Proposed Resource Management Plan ASQ (Allowable Sale Quantity) SYU (Sustained Yield Unit) ESC (Existing Stand Condition) M4C WPR_ID (a unique identifier generated in the options harvest model preparation...
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...
This paper compares the potential contribution of solar electric power in the form of photovoltaics to meet future US energy demand with the projected volume of oil estimated to be available in the Arctic National Wildlife Refuge. Such a comparison has practical value since it directly addresses a key policy choice under consideration in the new century, namely, that between one of the most promising untapped oil deposits in the world and one of the most rapidly growing renewable energy options. (C) 2003 Elsevier Ltd. All rights reserved.
Categories: Publication;
Types: Citation;
Tags: Arctic National Wildlife Refuge,
U.S.,
comparison,
electric,
electric power,
A new version of USGS’s FORE-SCE model was used to produce unprecedented landscape projections for four ecoregions in the Prairie Potholes region of Great Plains. The scenarios are consistent with the same scenarios modeled for the Great Plains Landscape Conservation Cooperative region. The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering approximately 350,000 square kilometers), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were...
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Climate Research and Development,
FORE-SCE,
Great Plains,
Great Plains,
Iowa,
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).
|
|