Jim Biard, Laura Stevens, Liqiang Sun, NCSU/CICS-NC
LOCA Scenarios for the Fourth National Climate Assessment (https://scenarios.globalchange.gov/loca-viewer/)
November 02, 2018

The accompanying files contain data derived from the Coupled Model Intercomparison Project Phase 5 (CMIP5), downscaled using Localized Constructed Analogs (LOCA), for a subset of climate variables. LOCA uses statistical techniques to correct global climate model data for biases and downscale those data to a 1/16th degree spatial resolution.

Data are available in netCDF format. There are three directories containing LOCA data for each variable for both the historical period (1950-2005) and future (2006-2099 or 2006-2100, model dependent) periods under the RCP4.5 and 8.5 scenarios. Within each directory there is one netCDF file for each of the 32 models.

LOCA derived climate variables available at this time are:
* consecDD: annual maximum number of consecutive dry days (days with total precipitation less than 0.01 inches)

The 32 CMIP5 models are:
ACCESS1-0, ACCESS1-3, bcc-csm1-1, bcc-csm1-1-m, CanESM2, CCSM4, CESM1-BGC, CESM1-CAM5, CMCC-CM, CMCC-CMS, CNRM-CM5, CSIRO-Mk3-6-0, EC EARTH, FGOALS-g2, GFDL-CM3, GFDL-ESM2G, GFDL-ESM2M, GISS-E2-H-p1, GISS-E2-R-p1, HadGEM2-AO, HadGEM2-CC, HadGEM2-ES, inmcm4, IPSL-CM5A-LR, IPSL-CM5A-MR, MIROC5, MIROC-ESM-CHEM, MIROC-ESM, MPI-ESM-LR, MPI-ESM-MR, MRI-CGCM3, NorESM1-M.

Ensemble averages for each grid cell should be calculated using a vector of model weights, using the values in "LOCA_weights.csv". These weights have been determined using the weighting strategy of Sanderson et al. (2017):
Sanderson, B. M., Wehner, M., and Knutti, R.: Skill and independence weighting for multi-model assessments, Geosci. Model Dev., 10, 2379-2395, https://doi.org/10.5194/gmd-10-2379-2017, 2017.

More information on CMIP5 can be found at: https://cmip.llnl.gov/cmip5/
More information on the LOCA dataset can be found at: http://loca.ucsd.edu/

Dataset citations:
Pierce, D.W., D.R. Cayan, and B.L. Thrasher, 2014: Statistical downscaling using Localized Constructed Analogs (LOCA), J. Hydrometeorology, 15, 2558-2585. doi:10.1175/JHM-D-14-0082.1
Pierce, D.W., D.R. Cayan, E.P. Maurer, J.T. Abatzoglou, and K.C. Hegewisch, 2015: Improved bias correction techniques for hydrological simulations of climate change. J. Hydrometeorology, 16, 2421-2442. doi:10.1175/JHM-D-14-0236.1

For additional information on this derived dataset, please contact:
Laura Stevens
North Carolina State University (NCSU)
Cooperative Institute for Climate and Satellites - North Carolina (CICS-NC) 
151 Patton Ave, Asheville, NC 28801
laura.stevens@noaa.gov
(828) 257-3006