P99  Migrating High Resource Post-Processing into WRF-ARW Code

Creighton, Glenn, Air Force Weather Agency

The Air Force Weather Agency (AFWA) now has the ability to run numerical weather prediction models at higher resolutions and over larger areas than ever.  However, as processors have become faster, data accessibility has lagged sorely behind.  The expected increase in demand for large, high spatial and temporal resolution simulations carries with it an implicit demand for more efficient data handling, especially in an environment like AFWA where bandwidth and I/O are such precious commodities.  With the advent of Mesoscale Ensemble Prediction Suite (MEPS) at AFWA, ignoring efficient data handling procedures during development would be a potentially crippling oversight.

Currently post-processing speed is still largely bottlenecked by the need to handle numerous large three-dimensional datasets.  It is proposed that this problem can be alleviated by implementing the strong message-passing interface architecture available within WRF.  In exchange for a marginal decrease in model processing speed, many of the three-dimensional datasets currently required by the MEPS post-processor, can be eliminated altogether and replaced with a comparatively lean set of two-dimensional diagnostics output from WRF itself.  This talk will outline some of the steps AFWA has taken to develop and insert diagnostics directly into WRF.