The Local Ensemble Transform Kalman Filter (LETKF) is an accurate state estimation scheme that has been applied successfully to several different weather and ocean models. I will address two issues in this talk. First, the LETKF is an embarrassingly parallel algorithm: every grid point is updated independently using a local set of observations. I will discuss some difficulties associated with getting good efficiency on modern parallel computer architectures. Second, I will discuss an approach to bias correction with potential application to atmospheric modeling.