• BLM REA COP 2010 Difference of Average Annual Temperature (2015-2030 vs 1968-1999) Simulated by RegCM3 with GENMOM Projections as Boundary Conditions (Western US)

    Metadata Updated: March 17, 2021

    Difference of Average Annual Temperature (2015-2030 vs 1968-1999) simulated by RegCM3 with GENMOM projections as boundary conditions. Units are degrees Celsius. These data were generated by the regional climate model RegCM3 with boundary conditions from a GCM future climate projections. The data were downscaled statistically by calculating differences (anomalies) between the RegCM3 results with GCM-driven boundary conditions for 1968-99 and those for a future period, in this case 2015-2030. The anomalies were added (temperatures) or multiplied (precipitation) to a climate baseline from PRISM (Parameter-elevation Regressions on Indepenent Slopes Model - prism.oregonstate.edu) data based on historical observations. The PRISM baseline was calculated as average monthly climate conditions for 1968-1999 reprojected the results to the BLM Albers 4km grid. PRISM data are provided in a 2.5 arc-minute lat-lon grid. This dataset represents the difference between the downscaled data for 2015-2030 and 1968-1999 means. RegCM3 is the third generation of the Regional Climate Model originally developed at the National Center for Atmospheric Research during the late 1980s and early 1990s. Details on current model components and applications of the model can be found in numerous publications (e.g., Giorgi et al, 2004a,b, Pal et al, 2007), the ICTP RegCNET web site (http://users.ictp.it/RegCNET/model.html), and the ICTP RegCM publications web site (http://users.ictp.it/~pubregcm/RegCM3/pubs.htm). The Western North America domain has a horizontal grid spacing of 15 km and 18 vertical levels. RegCM3 requires time-dependent lateral (wind, temperature, and humidity) and surface [surface pressure and sea surface temperature (SST)] boundary conditions that are updated every 6 hours of simulation. Lateral boundary conditions are derived from General Circulation Model (GCM) output or observations (e.g. NCEP). Additional information can be found at: http://regclim.coas.oregonstate.edu/. GENMOM is a recently developed GCM that includes components that have been applied extensively to climate research. The model is relatively low resolution (T31, ~3.75o x 3.75o) by design, a compromise that allows long simulations in reasonable time so that the model can be applied to paleoclimate experiments that commonly are run for multiple decades and centuries. GENMOM simulations of future climate were produced under the A2 emission scenario as part of a larger data-model comparison effort to test the ability of GCMs and RCMs to simulate North American climate and climatic variability in response to changes in global boundary conditions (e.g, insolation, atmospheric composition, continental ice sheets, sea level and paleogeography). Details and an evaluation of the model to simulate present-day climatology are given in Alder et al (2011).

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    Metadata Date September 15, 2016
    Metadata Created Date March 17, 2021
    Metadata Updated Date March 17, 2021
    Reference Date(s) January 1, 2011 (publication)
    Frequency Of Update notPlanned

    Metadata Source

    Harvested from BLM-COP

    Additional Metadata

    Resource Type Dataset
    Metadata Date September 15, 2016
    Metadata Created Date March 17, 2021
    Metadata Updated Date March 17, 2021
    Reference Date(s) January 1, 2011 (publication)
    Responsible Party Conservation Biology Institute (Point of Contact)
    Contact Email
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    Bbox East Long -106.745235
    Bbox North Lat 41.216248
    Bbox South Lat 35.481619
    Bbox West Long -114.446419
    Coupled Resource
    Frequency Of Update notPlanned
    Harvest Object Id e787587d-43db-4435-90da-de2eff58793c
    Harvest Source Id d15ec768-c7f1-4761-a8ba-b0f5ef9e28e5
    Harvest Source Title BLM-COP
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    Metadata Language eng; USA
    Metadata Type geospatial
    Progress completed
    Spatial Data Service Type
    Spatial Reference System
    Spatial Harvester True

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