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.

LOCA derived climate variables available at this time are:
* tavg: Daily average temperature (degrees Fahrenheit)
* tmax90F: Annual number of days > 90F (days)
* tmax95F: Annual number of days > 95F (days)
* tmax100F: Annual number of days > 100F (days)
* pr-annual: Annual total precipitation (inches)   
* pr1in: Annual number of days > 1 inch (days)
* pr-days-above-99th: Annual number of days with precipitation greater than the 99th percentile (days)
* pr-above-99th: Annual total precipitation greater than the 99th percentile (inches)

Data are available in ASCII (.txt) or CSV (.csv) format, and contain the following columns:
1. Longitude (decimal degrees)
2. Latitude (decimal degrees)
3. Historical Climate: Weighted multi-model mean for 1976-2005
4. Lower Emissions, Early 21st: Weighted multi-model mean for 2016-2045, under the RCP4.5 scenario
5. Lower Emissions, Mid 21st: Weighted multi-model mean for 2036-2065, under the RCP4.5 scenario 
6. Lower Emissions, Late 21st: Weighted multi-model mean for 2070-2099, under the RCP4.5 scenario
7. Higher Emissions, Early 21st: Weighted multi-model mean for 2016-2045, under the RCP8.5 scenario
8. Higher Emissions, Mid 21st: Weighted multi-model mean for 2036-2065, under the RCP8.5 scenario
9. Higher Emissions, Late 21st: Weighted multi-model mean for 2070-2099, under the RCP8.5 scenario

Multi-model mean values are weighted averages, using the following 32 CMIP5 model ensemble:
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 were calculated using a vector of model weights, 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