In complex terrain, surface observation sites are usually located in valleys. The analysis of surface data is made complicated by orographic features. Isotropy is a particularly questionable assumption.
This work develops a technique to try to utilize anisotropy and heterogeneity for objective analysis at the terrain-following lowest model level in mountainous regions. The goal is to improve the meso-scale details of lowest level analysis in complex terrain, with an ultimate goal of providing better input-fields for higher resolution numerical weather prediction model in such regions.
The technique developed here uses a mother-daughter approach to account for terrain effects in the analysis of surface data. The mother-daughter approach is incorporated into the analysis tool (the ARPS data assimilation system - ADAS) used in this study. The proposed approach and preliminary results and comparisons with other existing methods is presented.