Beatriz Navascués

Abstract: The analysis of surface variables and parameterization of surface processes of the reference HIRLAM system is described. Special emphasis has been put on the treatment of surface heterogeneity making that surface uxes of heat and momentum inherit such high spacial variability. The so called \tiling" approach has been adopted to prevent the problems associated with the use of e ective parameters in case of strongly changing surface conditions. The tiles are de ned by coupling independently each homogeneous patch or \tile" of a grid square to the lowest level of the model. Tiles interact each other only through the atmosphere. Average surface uxes are then computed by averaging surface uxes over each land-use tile weighted by their fractional area. The model allows up to ve di erent tiles (water, sea ice, bare ground, low vegetation, forest) within each grid square. Fractional snow cover is also allowed within each tile. The ISBA scheme has been selected to model land surface processes. The surface analysis initializes the following surface variables: sea surface temperature (SST), fraction of water and ice, snow depth, 2-metre temperature, 2-metre relative humidity, surface soil temperature, mean soil temperature, surface soil water content and total soil water content. The algorithm is able to cope with the tiled structure by averaging some variables only over land tiles. SST and snow depth analyses are based on the successive correction method. 2-metre temperature and relative humidity analyses are based on the optimal interpolation method. Finally, soil water content analysis is based on the sequential method, which corrects water content depending on 2-metre temperature and relative humidity forecast errors, only in those synoptic cases where screen variables are strongly in uenced by the surface beneath. A comprehensive list of parallel runs covering all seasons of the year have been conducted to demonstrate the superiority of the new package against the previous surface treatment. Special emphasis has been put on summer time and midlatitude regions were the in uence of soil water content on screen temperature and humidity is extremely high.

TL;DR: In this paper, a high-resolution probabilistic climate change projections for precipitation and temperature are generated by applying two statistical downscaling methods (regression for max and min temperatures, and analogue for precipitation) over the Pyrenees region in the frame of the CLIMPY project over a new high resolution (5 km × 5 km) observational grid using 24 climate models from CMIP5.

TL;DR: In this paper, the authors highlight the decisive role of international cooperation in the general progress achieved by the numerical weather prediction (NWP) area of research and highlight the main milestones of HIRLAM model development.

TL;DR: In this paper, a methodology for ensemble member's weighting of operational seasonal forecasting systems (SFS) based on an enhanced prediction of a climate driver strongly affecting meteorological parameters over a certain region is described.