Replication Data for: Vegetation Responses to 2012-2016 Drought in Northern and Southern California

Title: Monthly 4-km grids of self-calibrated Palmer Drought Severity Index (PDSIsc) for the Contiguous United States during 1895-2018 The 4-km self-calibrated PDSIsc data (1895-2018) were generated using an updated version of the dataset developed by Williams et al. (2015). For these PDSIsc calculations, potential evapotranspiration was calculated using the physically-based Penman-Monteith equation, which accounts for effects of temperature, humidity, wind speed, and net radiation (Allen, 1998; Monteith, 1965). Williams et al. (2015) calculated PDSIsc from a wide range of climate products. We use the PDSIsc records derived from precipitation and temperature data from Vose et al. (2014) to be consistent with NOAA climate division data, dew point data from PRISM (Daly et al., 2002; PRISM Climate Group, 2004), and wind speed and insolation data from the second phase of the North American Land Data Assimilation System (Mitchell et al., 2004), which are extended for years prior to 1979 using data from the Princeton Global Forcing (PGF) dataset (Sheffield et al. 2006). The PGF only goes back to 1901, so wind and solar data for 1895-1900 were set to the climatological means of 1921-2000. Each annual file is a .mat file (formatted for Matlab) that contains a data cube called “PDSIsc.” The 3-D data cube has dimensions of (1) latitude, (2) longitude, and (3) month. The PDSIsc values have been multiplied by 100 and rounded to save space. The lat and lon coordinates are as follows: Center of minimum latitude grid cell: 24.0625020664597 Center of minimum longitude grid cell: -125.020833333337 Grid cell resolution: 1/24 degrees Projection = longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0 References Allen, R. G., Pereira, L. S., Raes, D., Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome, 300(9), D05109. Daly, C., Gibson, W. P., Taylor, G. H., Johnson, G. L., Pasteris, P. (2002). A knowledge-based approach to the statistical mapping of climate. Climate research, 22(2), 99-113. Mitchell, K. E., Lohmann, D., Houser, P. R., Wood, E. F., Schaake, J. C., Robock, A., Cosgrove, B. A., Sheffield, J., Duan, Q., LLuo, L., Higgins, R. W., Pinker, R. T., Tarpley, J. D., Lettenmaier, D. P., Marshall, C. H., Entin, J. K., Pan, M., Shi, W., Koren, V., Meng, J., Ramsay, B. H., Bailey, A. A. (2004). The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system Journal of Geophysical Research, 109(D7), D07S90. Monteith, J. L. (1965). Evaporation and environment. Symoposia of the Society for Experimental Biology, 19, 205-234. PRISM Climate Group. (2004). PRISM Climate Data. Oregon State University, available at: http://prism.oregonstate.edu. Sheffield, J., Goteti, G., Wood, E. F. (2006). Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate, 19(13), 3088-3111. Vose, R. S., Applequist, S., Squires, M., Durre, I., Menne, M. J., Williams Jr., C. N., Fenimore, C., Gleason, K., Arndt, D. (2014). Improved historical temperature and precipitation time series for US climate divisions. Journal of Applied Meteorology and Climatology, 53(5), 1232-1251. Williams, A. P., Seager, R., Abatzoglou, J. T., Cook, B. I., Smerdon, J. E., Cook, E. R. (2015). Contribution of anthropogenic warming to California drought during 2012-2014. Geophysical Research Letters, 42, 6819-6828. doi:10.1002/2015GL064924