SRLCC Tabular Data (CSV files) - Monthly Precipitation

Dates

Publication Date: 2007

Summary

These data sets are subsets of the Maurer, et al. (2007) bias corrected, spatially downscaled monthly climate predictions 1 . The predictions were subsetted for the SRLCC and its ecoregions using the USGS Geo Data Portal or GDP (http://cida.usgs.gov/climate/gdp/). The GDP can calculate statistics of a gridded time series based on a particular area of interest (in this case, the uploaded shapefiles of the SRLCC and its ecoregions). After the input data sets (by Maurer, et al.) were processed through the GDP, the output CSV files contain tabular data for the SRLCC and individual ecoregions. Each value for precipitation in an output file is a mean across the SRLCC or ecoregion area. For a description of the GDP process, click here [...]

Summary

These data sets are subsets of the Maurer, et al. (2007) bias corrected, spatially downscaled monthly climate predictions 1 . The predictions were subsetted for the SRLCC and its ecoregions using the USGS Geo Data Portal or GDP ( http://cida.usgs.gov/climate/gdp/ ). The GDP can calculate statistics of a gridded time series based on a particular area of interest (in this case, the uploaded shapefiles of the SRLCC and its ecoregions).

After the input data sets (by Maurer, et al.) were processed through the GDP, the output CSV files contain tabular data for the SRLCC and individual ecoregions. Each value for precipitation in an output file is a mean across the SRLCC or ecoregion area. For a description of the GDP process, click here .

The CSV files in this ScienceBase item are the direct output of the GDP, without further work or analysis. (For graphs and data presented by month, see the ScienceBase folder Time series data presented in graphs (derived products, Excel files): SRLCC total area and ecoregions .

The CSV files here cover three emissions scenarios: b1 (low emissions and rate of change), a1b (middle) and a2 (high). Emission scenarios are possibilities for how the future will unfold in terms of greenhouse gas emissions, land use and other environmental factors 2 . Maurer et al.'s data set contains 16 General Circulation Models (GCMs), 3 of which were selected for inclusion in these subsets 3 . MIROC3.2 predicts temperatures at the high end of the spectrum (with a drier climate) and PCM1 predicts temperatures the low end (with a wetter climate). ECHAM5 was selected to represent the median ranges. Because of uncertainty and variation between projections, it is recommended to use more than one GCM for a climate analysis. Some analyses calculate 'ensembles' or averages of GCMs. For example, The Nature Conservancy's Climate Wizard tool can display an ensemble average of all 16 GCMs in Maurer, et al.’s 2007 data set (www.climatewizard.org).

1. Maurer, E. P., L. Brekke, T. Pruitt, and P. B. Duffy (2007), Fine-resolution climate projections enhance regional climate change impact studies, Eos Trans. AGU, 88(47), 504. Article available at http://www.agu.org/eos_elec/2007/47-504.html

2. Link to Special Report on Emissions Scenarios:
http://www.ipcc.ch/pdf/special-reports/spm/sres-en.pdf

3. Documentation for GCMs:
http://www-pcmdi.llnl.gov/ipcc/model_documentation/MIROC3.2_medres.htm
http://www-pcmdi.llnl.gov/ipcc/model_documentation/ECHAM5_MPI-OM.htm
http://www-pcmdi.llnl.gov/ipcc/model_documentation/PCM.htm

The ecoregion shapefile was downloaded from the Environmental Protection Agency’s website (metadata location: ftp://ftp.epa.gov/wed/ecoregions/us/Eco_Level_III_US.htm ) and shows level III ecoregions. Ecoregion areas were clipped to the boundary of the SRLCC.

Note: Dates in the GDP output files are in an ISO string, and will not be read by Excel as a date or number format. Here is an Excel equation (from the Geo Data Portal user interface FAQ section) that will convert the ISO date string to an Excel date number: =DATE(MID(A4,1,4),MID(A4,6,2),MID(A4,9,2))+TIME(MID(A4,12,2),MID(A4,15,2),MID(A4,18,2))

Contacts

Originator :: Edwin P Maurer, Levi D Brekke, Tom Pruitt, P. B. Duffy
Processor :: Tamar Norkin

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SRLCC_a1b_Precip_ECHAM5-MPI.csv	54.83 KB	text/plain
SRLCC_a1b_Precip_MIROC3.2(medres).csv	54.91 KB	text/plain
SRLCC_a1b_Precip_PCM-NCAR.csv	54.77 KB	text/plain
SRLCC_a2_Precip_ECHAM5-MPI.csv	54.82 KB	text/plain
SRLCC_a2_Precip_MIROC3.2(medres).csv	54.89 KB	text/plain
SRLCC_a2_Precip_PCM-NCAR.csv	54.77 KB	text/plain
SRLCC_b1_Precip_ECHAM5-MPI.csv	54.85 KB	text/plain
SRLCC_b1_Precip_MIROC3.2(medres).csv	54.86 KB	text/plain
SRLCC_b1_Precip_PCM-NCAR.csv	54.77 KB	text/plain
Ecoregions_a1b_Precip_ECHAM5-MPI.csv	289.89 KB	text/plain
Ecoregions_a1b_Precip_MIROC3.2(medres).csv	291.11 KB	text/plain
Ecoregions_a1b_Precip_PCM-NCAR.csv	289.41 KB	text/plain
Ecoregions_a2_Precip_ECHAM5-MPI.csv	289.89 KB	text/plain
Ecoregions_a2_Precip_MIROC3.2(medres).csv	291.18 KB	text/plain
Ecoregions_a2_Precip_PCM-NCAR.csv	289.5 KB	text/plain
Ecoregions_b1_Precip_ECHAM5-MPI.csv	289.98 KB	text/plain
Ecoregions_b1_Precip_MIROC3.2(medres).csv	290.65 KB	text/plain
Ecoregions_b1_Precip_PCM_NCAR.csv	289.19 KB	text/plain

SRLCC Tabular Data (CSV files) - Monthly Precipitation

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