Two different approaches for improving the representation of background error standard deviations have been developed and introduced into the HIRLAM high-resolution limited area model 3-D variational data assimilation scheme. One of the methods utilizes a horizontally varying climatological background error standard deviation field, estimated from a time-series of innovations. The second approach attempts to take temporal and spatial variations of the background error standard deviations into account by applying an Eady instability measure to the background field. The two approaches are described in detail and their functionality is demonstrated. Parallel data assimilation and forecasts experiments indicate a slightly positive impact on average verification scores, and in addition a positive impact is demonstrated for an individual synoptically active case.