Climate reconstructions for the SMPDSv1 modern pollen data set (Q10114)

The dataset contains estimates of three bioclimatic variables at modern pollen sites from the SMPDSv1 modern pollen data set (Harrison, 2019). The bioclimatic variables are mean temperature of the coldest month (MTCO), growing degree days above 0C (GDD0), and an annual Moisture Index, defined as the ratio of annual precipitation to annual potential evapotranspiration (MI). Estimates of these bioclimatic variables were derived using geographically-weighted regression of gridded climate data in order to correct for elevation differences between each pollen site and the corresponding grid cell. The climatological data (mean monthly temperature, precipitation, and fractional sunshine hours) were derived from the CRU CL v2.0 gridded dataset of modern (1961-1990) surface climate at 10 arc minute resolution (~18 km) (New et al., 2002).Geographically- weighted regression (GWR) was carried out in ArcGIS (v10.3, ESRI, 2014). A fixed bandwidth kernel of 1.06 (~140km) was used in the GWR because this optimized model diagnostics and reduced spatial clustering of residuals relative to other bandwidths. The climate of each pollen site was then estimated based on its longitude, latitude, and elevation. MTCO was taken directly from the GWR regression. GDD0were estimated from daily data using a mean-conserving interpolation of the monthly mean temperatures. MI was calculated for each pollen site using code modified from SPLASH v1.0 (Davis et al., 2017) based on daily values of precipitation, temperature and sunshine hours again obtained using a mean-conserving interpolation of the monthly values of each.