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The Standardized Precipitation Index (SPI) is a probability index that can be calculated for different time periods to indicate periods of abnormal wetness or dryness. SPI is derived solely from monthly precipitation and can be compared across regions with different climates. The SPI is an index based on the probability of recording a given amount of precipitation, and the probabilities are standardized so that an index of zero indicates the median precipitation amount (half of the historical precipitation amounts are below the median, and half are above the median). This dataset shows the average 12-month SPI (in classes ranging from extremely wet to extremely dry) for the three-month forecast period indentified...
MC1 is a dynamic vegetation model for estimating the distribution of vegetation and associated ecosystem fluxes of carbon, nutrients, and water. It was created to assess the potential impacts of global climate change on ecosystem structure and function at a wide range of spatial scales from landscape to global. The model incorporates transient dynamics to make predictions about the patterns of ecological change. MC1 was created by combining physiologically based biogeographic rules defined in the MAPSS model with a modified version of the biogeochemical model, CENTURY. MC1 includes a fire module, MCFIRE, that mechanistically simulates the occurrence and impacts of fire events. Climate input data sources for this...
This dataset shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using National Fire Danger Rating System (NFDRS) formulas, monthly climatic (temperature, precipitation, and relative humidity) data, and fuel moisture and loading estimates. Monthly climatic data includes recorded values up to the last observed...
Winter (January – March) precipitation averaged over 2046-2065 from the general circulation model PCM1 (Washington et al. 2000; Meehl et al. 2003) under the A2 emission scenario with a grid cell size of 10 km x 10km. References: Meehl, G.A., W.M. Washington, T.M.L. Wigley, J.M. Arblaster, and A. Dai. 2003. Solar and greenhouse gas forcing and climate response in the twentieth century. J Climate 16:426–444. Washington, W.M., J.W. Weatherly, G.A. Meehl, A.J. Semtner, T.W. Bettge, A.P. Craig, W.G. Stran, J. Arblaster, V.B. Wayland, R. James , and Y. Zhang. 2000. Parallel climate model (PCM) control and transient simulations. Clim Dyn 16: 755–774.
This map shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). Different colors indicate the level of consensus among five different MC1 simulations (i.e., one for each forecast provided by five different weather models), ranging from one of five to five of five simulations predicting high fire potential. The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using...
The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
Winter (January – March) precipitation (mm) averaged over 2046-2065 from the general circulation model Hadley CM3 (Gordon et al. 2000, Pope et al. 2000) downscaled to a grid cell size of 10 km x 10km. References: Gordon C., C. Cooper , C.A. Senior, H. Banks, J.M. Gregory, T.C. Johns , J.F.B. Mitchell, and R.A. Wood. 2000. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim Dyn 16:147–168. Pope, V.D., M.L. Gallani, P.R. Rowntree, and R.A. Stratton. 2000. The impact of new physical parameterisations in the Hadley Centre climate model – HadAM3. Clim Dyn 16:123–146.
Future (2046-2065) predicted probability of fisher year-round occurrence projected under the A1fi emissions scenario with the Hadley CM3 GCM model (Gordon et al. 2000, Pope et al. 2000). Projected fisher distribution was created with Maxent (Phillips et al. 2006) using fisher detections (N = 102, spanning 1993 – 2011) and seven predictor variables: mean winter (January – March) precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean daily low temperature for the month of the year with the warmest mean daily low temperature, mean fraction of vegetation carbon burned, mean vegetation carbon (g C m2), and modal vegetation class. Predictor variables had a grid cell size of...
Description: Predicted probability of fisher year-round occurrence created with Maxent (Phillips et al. 2006) using fisher detections (N = 102, spanning 1993 – 2011) and seven predictor variables: mean winter (January – March) precipitation, mean summer (July – September) precipitation, mean summer temperature amplitude, mean daily low temperature for the month of the year with the warmest mean daily low temperature, mean fraction of vegetation carbon burned, mean vegetation carbon (g C m2), and modal vegetation class. Predictor variables had a grid cell size of 10 km, vegetation variables were simulated with MC1 (Hayhoe et al. 2004) and climate variables were provided by the PRISM GROUP (Daly et al. 1994). This...
The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
This map shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). Different colors indicate the level of consensus among five different MC1 simulations (i.e., one for each forecast provided by five different weather models), ranging from one of five to five of five simulations predicting high fire potential. The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using...
The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
This dataset shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using National Fire Danger Rating System (NFDRS) formulas, monthly climatic (temperature, precipitation, and relative humidity) data, and fuel moisture and loading estimates. Monthly climatic data includes recorded values up to the last observed...
Annual precipitation (mm) averaged over 1986 – 2005, simulated by the MC1 dynamic global vegetation model (Bachelet et al. 2001) at a 4 km x 4 km spatial resolution using PRISM climate for the historical period. This effort is part of a pilot project to apply and evaluate the Yale Framework (Yale Science Panel for Integrating Climate Adaptation and Landscape Conservation Planning). Note: The MC1 model is described in data basin (http://databasin.org/climate-center/features/mc1-dynamic-global-vegetation-model).
Simulated fraction of vegetation carbon in forest averaged over 2076-2095 simulated by the MC1 dynamic global vegetation model (Bachelet et al. 2001) at a 800 m x 800 m spatial resolution using future climate projections provided through CMIP3 (http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php). Future climate drivers were generated using statistical downscaling (simple delta method) of general circulation model projections, in this case Hadley CM3 (Johns et al. 2003) under the A2 emission scenario (Naki?enovi? et al. 2000). The deltas (differences for temperatures and ratios for precipitation) were used to modify PRISM 800 m historical baseline (Daly et al. 2008). Note: The MC1 model is described in data basin...
Simulated fraction of vegetation carbon in forest averaged over 2046-2065 simulated by the MC1 dynamic global vegetation model (Bachelet et al. 2001) at a 800 m x 800 m spatial resolution using future climate projections provided through CMIP3 (http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php). Future climate drivers were generated using statistical downscaling (simple delta method) of general circulation model projections, in this case CSIRO Mk3 A2 (Gordon 2002) under the A2 emission scenario (Naki?enovi? et al. 2000). The deltas (differences for temperatures and ratios for precipitation) were used to modify PRISM 800 m historical baseline (Daly et al. 2008). Note: The MC1 model is described in data basin (http://databasin.org/climate-center/features/mc1-dynamic-global-vegetati...
This map represents the change between 1971-2000 and 2070-2099 in the mean annual fraction of each gridcell affected by fire, as simulated by the model MC1 under the Hadley future climate projection and A2 anthropogenic emissions scenario. Data values are calculated as PART_BURN(2070-2099) minus PART_BURN(1971-2000). PART_BURN data is from MC1 version B60. The average annual fraction of cell burned for the respective 30-year periods increased in some of the 5,311 grid cells of the Apache-Sitgreaves study area and decreased in others. The range of data values is from -0.077 to +0.163. The mean value is +0.031. The vegetation model MC1 (e.g. Bachelet et al. 2001) was used to simulate vegetation dynamics, associated...
MC1 is a dynamic vegetation model for estimating the distribution of vegetation and associated ecosystem fluxes of carbon, nutrients, and water. It was created to assess the potential impacts of global climate change on ecosystem structure and function at a wide range of spatial scales from landscape to global. The model incorporates transient dynamics to make predictions about the patterns of ecological change. MC1 was created by combining physiologically based biogeographic rules defined in the MAPSS model with a modified version of the biogeochemical model, CENTURY. MC1 includes a fire module, MCFIRE, that mechanistically simulates the occurrence and impacts of fire events. Climate input data sources for this...
The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
The Standardized Precipitation Index (SPI) is a probability index that can be calculated for different time periods to indicate periods of abnormal wetness or dryness. SPI is derived solely from monthly precipitation and can be compared across regions with different climates. The SPI is an index based on the probability of recording a given amount of precipitation, and the probabilities are standardized so that an index of zero indicates the median precipitation amount (half of the historical precipitation amounts are below the median, and half are above the median). This dataset shows the average 12-month SPI (in classes ranging from extremely wet to extremely dry) for the three-month forecast period indentified...
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