2012 Fundamental & Computational Sciences Accomplishments Report Now Available
Since 2004, the Fundamental & Computational Sciences Directorate publishes a full-color brochure that highlights discoveries and solutions made during the fiscal year. 2012 Key Accomplishments Report of the Fundamental & Computational Sciences is now available as a downloadable PDF.
PNNL Researchers Awarded Best Paper at International Conference
Congratulations to Alessandro Morari and Roberto Gioiosa, computational research scientists at Pacific Northwest National Laboratory, on winning the best paper award at the International Parallel & Distributed Process Symposium (IPDPS) in China. Their paper "Evaluating the impact of TLB misses on future HPC systems" was named best paper in the software category.
Guang Lin Honored with Early Career Achievement Award
Congratulations to Guang Lin, a computational mathematics researcher at Pacific Northwest National Laboratory, on being selected to receive the Laboratory Director's 2012 Ronald L. Brodzinski Award for Early Career Exceptional Achievement. He was recognized for his leading research in uncertainty quantification and petascale data analytics applied to climate models.
Katrina Hui Named Semi-Finalist in Intel Science Talent Search
Congratulations to Katrina Hui, a high school science intern in Pacific Northwest National Laboratory's Computational Sciences & Mathematics Division, on being named a semi-finalist in the Intel Science Talent Search. Andrey Sushko, another PNNL high school intern, received second place honors.
Taming Uncertainty in Climate Prediction
Uncertainty just became more certain. Atmospheric and computational researchers at Pacific Northwest National Laboratory used a new scientific approach called "uncertainty quantification," or UQ, that allowed them to better simulate precipitation. Their study is the first to apply a stochastic sampling method to select model inputs for precipitation representations and improve atmospheric simulations within a regional weather research and forecasting model.
