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A technique,is developed,to anisotropically spread surface observations,in steep valleys. The goal is to create an improved objective analysis for the lowest, terrain-following numerical weather prediction (NWP) model,level in mountainous,terrain. The method is a mother–daughter (MD) approach, where the amount of information transferred from one grid point (the mother) to all neighboring,grid points (the daughters) depends,on elevation differences. The daughters,become,mothers,and further share information,with their neighboring,grid points. This iterative method allows information to follow valleys around ridges, while reducing spread over the ridge top. The method,is further refined to account,for land–sea anisotropy. This approach,is tested in the objective analyses of surface potential temperatures,over the steep moun- tainous and coastal terrain of southwestern British Columbia, Canada. Analysis results are compared with other existing schemes,using the Advanced,Regional Prediction System Data Assimilation System (ADAS). It is found that the MD approach,outperforms,the other schemes,over mountainous,and coastal terrain.

A Mesoscale Analysis Method for Surface Potential Temperature in Mountainous and Coastal Terrain