Do high resolution GCMs overestimate precipitation over land?
Authors: Müller Omar , Vidale Pier Luigi , McGuire Patrick , Vannière Benoît , Schiemann Reinhard , Peano Daniele 
Published: March 2020

&lt;p&gt;Previous studies showed that high resolution GCMs overestimate land precipitation when compared against gridded observations or reanalysis (Demory et al. 2014, Vanni&amp;#232;re et al. 2019). In particular, grid point models (eg. HadGEM3) show a significant increase of precipitation on regions dominated by complex orography, where the scarcity of gauge stations increase the uncertainty of gridded observations. The goal of this work is to assess the effect of such differences in precipitation on river discharge, considering it as an integrator of the water balance at catchment scale. A set of JULES and CLM simulations have been conducted turning rivers on with Total Runoff Integrating Pathways (TRIP) and the River Transport Model (RTM) respectively. The simulations form three ensembles for each land surface model (LSM) which main difference is given by the forcing dataset. The forcings are WFDEI (reanalysis), LR (~1&amp;#176; resolution in meteorological data from GCMs) and HR (~0.25&amp;#176; resolution in meteorological data from GCMs). These ensembles are evaluated in a set of 280 catchments distributed around the world.&lt;/p&gt;&lt;p&gt;In terms of correlation between simulated and observed river discharge observations, the results show that LSMs forced by reanalysis have higher performance than LSMs forced by GCMs as expected. In terms of biases, the river discharge is underestimated in eight out of eleven major basins when LSMs are forced by reanalysis. On those basins, the extra precipitation estimated by GCMs help to simulate an amount of river discharge closer to observations (Eg. Yenisey and Lena). Moreover, 37 small basins with a strong component of orographic precipitation over the Andes, the Rocky Mountains, the Alps and in the Maritime Continent were evaluated. In most cases HR offers notably better results than LR and WFDEI, suggesting that high resolution models produce orographic precipitation in the correct place and time.&lt;/p&gt;&lt;p&gt;In future works offline TRIP simulations will be carried out directly forced by runoff and subsurface runoff from GCMs. It will allow to discard errors in evapotranspiration produced by JULES or CLM when they are used to simulate river discharge. This work is part of the European Process-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment (PRIMAVERA) Project. PRIMAVERA is a collaboration between 19 funded by the European Union&amp;#8217;s Horizon 2020 Research &amp; Innovation Programme.&lt;/p&gt;&lt;p&gt;Demory, M. E., Vidale, P. L., Roberts, M. J., Berrisford, P., Strachan, J., Schiemann, R., &amp; Mizielinski, M. S. (2014). The role of horizontal resolution in simulating drivers of the global hydrological cycle.&amp;#160;CLIM DYNAM,&amp;#160;42(7-8), 2201-2225.&lt;/p&gt;&lt;p&gt;Vanni&amp;#232;re, B., Demory, M. E., Vidale, P. L., Schiemann, R., Roberts, M. J., Roberts, C. D., ... &amp; Senan, R. (2018). Multi-model evaluation of the sensitivity of the global energy budget and hydrological cycle to resolution.&amp;#160;CLIM DYNAM, 1-30.&lt;/p&gt;