610 The Effects of Numerical Noise on Perturbation Experiments

Tuesday, 24 January 2017
4E (Washington State Convention Center )
Brian C. Ancell, Texas Tech Univ., Lubbock, TX

Handout (386.9 kB)

Perturbation experiments are used widely within numerical weather prediction models  to investigate the effects of initial condition error and data assimilation on atmospheric forecasts.  It has been discovered that perturbations within the Weather Research and Forecasting (WRF) model create numerical noise that propagates horizontally at speeds substantially faster than any realistic physical mode.   This noise is very small, and likely does not affect the atmospheric state within model simulations in areas where dry dynamics dominate.  However, in areas of moist convection or precipitation, the noise can grow rapidly through chaotic processes to significantly alter the state, potentially growing upscale.  The growth of noise thus has the ability to cause a misinterpretation of the realistic effects of the perturbation in the first place.  This work details the propagation and growth of numerical noise in the WRF model for a simulation of convection, and compares it to a number of perturbation experiments for which realistic perturbation growth is expected.  The implications of these results in the greater body of literature is discussed.
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