Climate projections downscaled with statistical methods often focus on precipitation (P) and temperature (T) variables, which is not sufficient to run offline land surface models (LSMs) and derive hydrological projections based on both water and energy budgets. This work extends a proposition by Clemins et al. (2019) to build on a multivariate high-resolution reanalysis dataset to infer projected ancillary variables from P & T projections based on analogue resampling. The refined method is a multisite and multivariate resampling method based on analogy of spatially distributed P & T daily anomalies. Anomalies are derived with respect to a baseline monthly climatology. The method thus makes use of spatial and multivariate consistency available in the archive reanalysis to supplement projections for additional variables and for a possibly extended spatial domain. The baseline climatology is considered as linearly transient for temperature variables to deal with anomalies not experienced during the archive period, and large-scale additional transient changes in T are passed on ancillary variables based on present-day anomaly relationships. The new proposed method is exemplified for the Greater Pyrenean Region (GPR) defined as all basins draining the Pyrenees mountain range and extending over France, Spain, and Andorra. The archive reanalysis used here is the 2.5 km gridded SAFRAN-PIRAGUA surface reanalysis for the Pyrenees over 1965-2005 derived from existing SAFRAN reanalyses over France (Vidal et al., 2010) and Spain (Quintana-Seguí et al., 2017). The projections considered here are 6 CMIP5 GCMs run under both RCP4.5 and RCP8.5 previously downscaled and including only P, TN, and TX variables and not available north of the Pyrenees (Amblar Francés et al., 2020). Applying the resampling method over the GPR led to 2.5 km gridded projections of daily time series of all variables required by LSMs. Results show – on top of an increasing temperature and a decreasing precipitation over the 21st century – a decrease in wind speed, relative humidity, and infrared radiation, and an increase in visible radiation and evapotranspiration. These projections come with a large inter-GCM dispersion and more pronounced changes under RCP8.5 This work was funded by the Interreg V-A POCTEFA 2014-2020 through the EFA210/16 PIRAGUA project. Amblar-Francés, M. P., Ramos-Calzado, P., Sanchis-Lladó, J., Hernanz-Lázaro, A., Peral-García, M. C., Navascués, B., Dominguez-Alonso, M., Pastor-Saavedra, M. A. & Rodríguez-Camino, E. (2020) High resolution climate change projections for the Pyrenees region. Advances in Science and Research, 17, 191-208 Clemins, P. J., Bucini, G., Winter, J. M., Beckage, B., Towler, E., Betts, A., Cummings, R. & Chang Queiroz, H. (2019) An analog approach for weather estimation using climate projections and reanalysis data. Journal of Applied Meteorology and Climatology, 58, 1763-1777 Quintana-Seguí, P., Turco, M., Herrera, S. & Miguez-Macho, G. Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim (2017) Hydrology and Earth System Sciences, 21, 2187-2201 Vidal, J.-P., Martin, E., Franchistéguy, L., Baillon, M. & Soubeyroux, J.-M. A 50-year high-resolution atmospheric reanalysis over France with the Safran system (2010) International Journal of Climatology, 30, 1627-1644