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The Weather Research and Forecast (WRF) model is a limitedarea model of the atmosphere for mesoscale research and operational numerical weather prediction (NWP). A petascale problem is a WRF nature run that provides very high-resolution "truth" against which more coarse simulations or perturbation runs may be compared for purposes of studying predictability, stochastic parameterization, and fundamental dynamics. We carried out a nature run involving an idealized high resolution rotating fluid on the hemisphere to investigate scales that span the k-3 to k-5/3 kinetic energy spectral transition of the observed atmosphere using 65,536 processors of the BG/L machine at LLNL. We worked through issues of parallel I/O and scalability. The primary result is not just the scalability and high Tflops number, but an important step towards understanding weather predictability at high resolution.

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A B S T R A C TParameter uncertainty in atmospheric model forcing and closure schemes has motivated both parameter estimation with data assimilation and use of pre-specified distributions to simulate model uncertainty in short-range ensemble prediction. This work assesses the potential for parameter estimation and ensemble prediction by analysing 2 months of mesoscale ensemble predictions in which each member uses distinct, and fixed, settings for four model parameters. A space-filling parameter selection design leads to a unique parameter set for each ensemble member. An experiment to test linear scaling between parameter distribution width and ensemble spread shows the lack of a general linear response to parameters. Individual member near-surface spatial means, spatial variances and skill show that perturbed models are typically indistinguishable. Parameter-state rank correlation fields are not statistically significant, although the presence of other sources of noise may mask true correlations. Results suggest that ensemble prediction using perturbed parameters may be a simple complement to more complex model-error simulation methods, but that parameter estimation may prove difficult or costly for real mesoscale numerical weather prediction applications.

The University of Wyoming King Air aircraft was the primary instrument platform for turbulence measurements in the bottom half of the convective boundary layer during 15 July-13 August 1996. A total of 12 successful research flights were made, each of about 4.5-h duration. Crosswind (east-west) flight patterns were flown in Oklahoma and Kansas over three sites of different land use: forest, pasture, and crops.Measurements of mean values, turbulent deviations, and turbulent fluxes of temperature, moisture, and momentum were made to test theories of convective transport, the radix layer, and cumulus potential. Additional portions of each flight included slant soundings and near-surface horizontal flights in order to determine mixed layer (ML) scaling variables such as ML depth z., Deardorff velocity and buoyancy velocity wR. While the ML was shallower and the ground wetter than anticipated based on climatology, a high-quality dataset was obtained.