Use of an OSSE to estimate the characteristics of analysis error

Ronald Errico


Observation system simulation experiments have been performed at the National Centers for Environmental Prediction primarily for the purpose of evaluating the forecast improvement potential of proposed new observation instruments. Validation of the simulations have been conducted primarily by comparing results from corresponding data denial experiments in both simulated and real data assimilation contexts. Additional validation is presented here using comparisons of some statistics of analysis increments determined from a baseline simulation using the entire suite of observations utilized during a reanalysis for February 1993. By exploiting the availability of a data set representing "truth" in the simulations, the background and analysis errors produced for the baseline simulation are computed. Several statistics of these errors are then determined, including time means and variances as functions of location or spherical harmonic wave number, vertical correlations, Kalman gains, and balance as measured by projections onto normal modes. Use of an OSSE in this way is one of the few means of estimating analysis error characteristics. Although this work with the present NCEP OSSE should not be considered definitive, it reveals some important ways in which OSSEs may be utilized beyond their original purposes.